PRIORITY INFORMATION
[001] This patent application does not claim priority from any application.
TECHNICAL FIELD
[002] The present subject matter described herein, in general, relates to communication networks, and more particularly a system and a method for creating an attribute set for a search string of a user in the communication networks.
BACKGROUND
[003] In general, many data sources with loads of information are currently available on communication networks, such as the Internet. These data sources are typically positioned in unstructured and heterogeneous environment in the communication networks. Also, with commercialization of these communication networks, the growth of available information in the data sources has substantially increased.
[004] Typically, a user uses one or more search engines in the communication networks to access required information from these data sources. In particular, a user may submit a search query through a search engine to locate information related to a topic of his interest in these data sources. In response to the submitted search query, the user receives multiple search results from the data sources available in the communication networks. Further, each search result includes a title, a brief description, and a web address linked to a corresponding data source in the communication networks. However, for the user to locate information related to his interest, the user may have to browse contents of more than one of these data sources at a time. Also, the information or contents may be of different types in different formats, such as articles, documents, events, and/or products. Moreover, accessing information from the data sources in unstructured and heterogeneous environment is a complex process. As a result, the user struggles to find timely and relevant information as they are not easily identified. In some cases, the user even fails to access relevant information because it requires a significant amount of time, effort, and cost to conduct an exhaustive search of all the results to identify those most likely of interest to the user.
[005] Thus, there is a need for the system and the method to combine data of different types from multiple data sources located in unstructured and heterogeneous environment to reduce the above-mentioned complexities. Also, there is a need for a system and a method to collect data from different data sources and customize the data according to user’s unique interests, regardless of the number of data sources and layout/format of the data in these data sources.
SUMMARY
[006] Before the present system(s) and methods, are described, it is to be understood that this application is not limited to the particular system(s), and methodologies described, as there can be multiple possible embodiments which are not expressly illustrated in the present disclosures. It is also to be understood that the terminology used in the description is for the purpose of describing the particular implementations or versions or embodiments only, and is not intended to limit the scope of the present application. This summary is provided to introduce aspects related to a system and a method for creating an attribute set for a search string of a user. This summary is not intended to identify essential features of the claimed subject matter nor is it intended for use in determining or limiting the scope of the claimed subject matter.
[007] In one implementation, a system for creating an attribute set for a search string of a user is disclosed. In one aspect, the system includes an interface unit configured to receive the search string of the user. Also, the system includes a processing sub-system communicatively coupled to the interface unit and configured to create the attribute set including a plurality of attributes and corresponding attribute values based on the received search string and pre-stored personalized data of the user. The attributes and the corresponding attribute values are extracted from multiple data sources located in unstructured and heterogeneous environment. Furthermore, the system includes a display unit electrically coupled to the processing sub-system and configured to display an object including the attribute set having the attributes and the corresponding attribute values referenced to the multiple data sources.
[008] In another implementation, a method for creating an attribute set for a search string of a user is disclosed. In one aspect, the method includes receiving, by an interface unit, the search string of the user. Also, the method includes creating, by a processing sub-system, an attribute set including a plurality of attributes and corresponding attribute values based on the received search string and pre-stored personalized data of the user. The attributes and the corresponding attribute values are extracted from multiple data sources located in unstructured and heterogeneous environment. Further, the method includes displaying, by a display unit, an object including the attribute set having the attributes and the corresponding attribute values referenced to the multiple data sources.
[009] In yet another implementation, non-transitory computer readable medium storing instructions executable by a processing system to perform a method is disclosed. The method includes receiving, by an interface unit, a search string of a user. Also, the method includes creating, by a processing sub-system, an attribute set including a plurality of attributes and corresponding attribute values based on the received search string and pre-stored personalized data of the user. The attributes and the corresponding attribute values are extracted from multiple data sources located in unstructured and heterogeneous environment. Further, the method includes displaying, by a display unit, an object including the attribute set having the attributes and the corresponding attribute values referenced to the multiple data sources.
BRIEF DESCRIPTION OF THE DRAWINGS
[010] The foregoing detailed description of embodiments is better understood when read in conjunction with the appended drawings. For the purpose of illustrating of the present subject matter, an example of construction of the present subject matter is provided as figures; however, the invention is not limited to the specific method and system disclosed in the document and the figures.
[011] The present subject matter is described detail with reference to the accompanying figures. In the figures, the left-most digit(s) of a reference number identifies the figure in which the reference number first appears. The same numbers are used throughout the drawings to refer various features of the present subject matter.
[012] FIG. 1 is a diagrammatical representation of a system for creating an attribute set for a search string of a user, in accordance with an embodiment of the present subject matter;
[013] FIG. 2 is a block diagram of the system including a processing sub-system communicating with multiple data sources, in accordance with an embodiment of the present subject matter; and
[014] FIG. 3 is a flow chart illustrating a method for creating the attribute set for the search string of the user, in accordance with an embodiment of the present subject matter.
DETAILED DESCRIPTION
[015] As will be described in detail hereinafter, various embodiments of systems and methods for creating an attribute set with associated attribute values for a search string received from a user is presented. In particular, the systems and methods presented herein identifies at least one entity that is most likely to be of interest to the user based on the received search string. Further, at least one entity-dimension for the identified entity is determined. Thereafter, the systems and the methods create the attribute set including the attributes and the corresponding attribute values related to the determined entity-dimension based on the search string and the pre-stored personalized data associated with the user. These attributes and the corresponding attribute values may be obtained by combining data scattered in different data sources. Also, this created attribute set is constructed and displayed as an object in a predefined structure to form one search result to the user.
[016] Some embodiments of this disclosure, illustrating all its features, will now be discussed in detail. The words “comprising,” “having,” “containing,” and “including,” and other forms thereof, are intended to be equivalent in meaning and be open ended in that an item or items following any one of these words is not meant to be an exhaustive listing of such item or items, or meant to be limited to only the listed item or items. It must also be noted that as used herein and in the appended claims, the singular forms “a,” “an,” and “the” include plural references unless the context clearly dictates otherwise. Although any system and methods similar or equivalent to those described herein can be used in the practice or testing of embodiments of the present disclosure, the exemplary, system and methods are now described. The disclosed embodiments are merely examples of the disclosure, which may be embodied in various forms. Various modifications to the embodiment will be readily apparent to those skilled in the art and the generic principles herein may be applied to other embodiments. However, one of ordinary skill in the art will readily recognize that the present disclosure is not intended to be limited to the embodiments described, but is to be accorded the widest scope consistent with the principles and features described herein.
[017] As used herein, the term “non- transitory computer readable media” is intended to be representative of any tangible computer-based device implemented in any method or technology for short-term and long-term storage of information, such as, computer-readable instructions, data structures, program modules and sub-modules, or other data in any device. Therefore, the methods described herein may be encoded as executable instructions embodied in a tangible, non-transitory, computer readable medium, including, without limitation, a storage device and/or a memory device. Such instructions, when executed by a processor, cause the processor to perform at least a portion of the methods described herein. Moreover , as used herein , the term “ non transitory computer-readable media ” includes all tangible , computer-readable media , including , without limitation , non-transitory computer storage devices , including , without limitation , volatile and nonvolatile media , and removable and non-removable media such as a firmware , physical and virtual storage , CD-ROMs , DVDs , and any other digital source such as a network or the Internet , as well as yet to be developed digital means, with the sole exception being a transitory, propagating signal .
[018] As used herein, the terms “software” and “firm ware” are interchangeable, and include any computer program stored in memory for execution by devices that include, without limitation, mobile devices, clusters, personal computers, workstations, clients, and servers.
[019] As used herein, the term “processing sub-system” and related terms, e.g., “computing device”, are not limited to integrated circuits referred to in the art as a computer, but broadly refers to at least one microcontroller, microcomputer, programmable logic controller (PLC), application specific integrated circuit, and other programmable circuits, and these terms are used interchangeably herein.
[020] Referring now to Figure 1, a diagrammatical representation of a system 100 for creating an attribute set for a search string of a user, in accordance with an embodiment of the present subject matter may be described. The system 100 includes an interface unit 102, a processing sub-system 104, a display unit 106, and multiple data sources 108. Also, the processing sub-system 104 may be communicatively coupled to other data sources via communication network. It may be noted that the system 100 may include other components and is not limited to the components shown in FIG. 1.
[021] In a presently contemplated configuration, the multiple data sources 108 may include personal data sources and search history 110, domain specific data sources and domain specific search history 112, and public and private data sources 114. The personal data sources and search history 110 may include data related to preferences or pre-stored personalized data of the user. In one example, the personalized data may include a profile of the user, such as name, profession, date/place of birth, social identity, employee identity, interest areas and other similar details of the user. Further, the search history may include information related to search strings, search pattern of the user, frequently and/or recently visited data sources and other similar searched data of the user. Also, these data sources 110 are the first area where the specification, template, and/or attributes related to an entity will be searched. Moreover, these data sources 110 can be considered as a self-learning part where a new specification, a new template, and/or new attributes will be updated for any future reference.
[022] In a similar manner, the domain specific data sources and domain specific search history 112 may include data related to a domain of the user. This domain may be referred to an area that the user is working or interested. For example, if the user is a gynecologist or a pediatrician, the domain of the user may be referred to as a medical domain. Similarly, if the user is a service engineer, the domain of the user may be referred to as a mechanical domain. In one embodiment, the domain specific data sources and domain specific search history 112 may include reference repositories where the information is stored in the format of document, pdf, images, database, etc. Also, these data sources 112 are the second area where the specification, template, and/or attributes related to the entity will be searched. Moreover, this area be referred as a heterogeneous environment local system, FTPs, cloud environment, and/or common repository.
[023] Furthermore, the public and private data sources 114 may include data related to a public or general domain. Data in this area will be available in World Wide Web (WWW), which can be retrieved through web crawler, rest services, web services, etc. These data source 114 will be the final reference area where the entity, attribute, and attribute values are searched. In one example, public and private data sources 114 may include multiple data sources that are located in an unstructured and heterogeneous environment. In one example, the unstructured and heterogeneous environment may be referred to an environment where the multiple sources are present in different assorted locations and data in these sources will be in an unstructured pattern or a combination of structured and unstructured patterns.
[024] As depicted in FIG. 1, the interface unit 102 is communicatively coupled to the processing sub-system 104. The interface unit 102 may be an input-output device (I/O) that is capable of receiving a search string from a user. In one embodiment, the search string may include a text pattern of the user. In one example, the text pattern may be defined as a combination of characters arranged in a meaningful format. Further, the interface unit 102 may transmit the received search string to the processing sub-system 104.
[025] In the conventional or existing systems, a user submits a search query through a search engine to locate information related to a topic of his interest. In response to the submitted search query, the user receives multiple search results, where each search result includes a title, a brief description, and a web address linked to a corresponding data source. Further, the user needs to browse contents of more than one of these data sources at a time. Also, the contents may be in different formats, such as articles, documents, events, and/or products. As a result, the user struggles to find timely and relevant information as they are not easily identified. In some cases, the user even fails to access relevant information because it requires a significant amount of time, effort, and cost to conduct an exhaustive search of all the results to identify those most likely to be of interest to the user.
[026] To overcome the above problems/shortcomings, the exemplary system 100 includes the processing sub-system 104 that is used to collate and consolidate search results as an object specific to the user or the domain of the user. The object may be referred to as a predefined template, format, or structure where attributes and corresponding attribute values are arranged in a fashion that is easily readable and accessible by the user.
[027] In a presently contemplated configuration, the processing sub-system 104 is communicatively coupled to the interface unit 102, the display unit 106, and the multiple data sources 108. In one example, the processing sub-system 104 may include one or more search engines that are capable of extracting data/information from communication networks. Further, the processing sub-system 104 may receive the search string from the user via the interface unit 102. In one example, the search string may be a text pattern related to the information or content that the user is searching for in the communication networks.
[028] Based on the search string entered by the user, the processing sub-system 104 may obtain pre-stored personalized data or preferences of the user from the multiple data sources 108. In one example, the processing sub-system 104 may obtain the profile of the user from the personal data sources and the information related to the search strings, the search pattern of the user, frequently and/or recently visited data sources from the search history. Similarly, the processing sub-system 104 may obtain the domain of the user from the domain specific data sources. Thereafter, the processing sub-system 104 may extract data from these multiple data sources to create an attribute set based on the received search string and the pre-stored personalized data and domain of the user. In particular, the attributes and the corresponding attribute values are extracted from multiple data sources located in unstructured and heterogeneous environment. Further, these extracted attributes and corresponding attribute values are collated and consolidated to create the attribute set. It may be noted that the aspect of creating the attribute set will be explained in greater detail with respect to FIG. 2.
[029] Upon creating the attribute set, the processing sub-system 104 may construct an object including the attribute set. Thereafter, the processing sub-system 104 may display the constructed object on the display unit 106 so that the user can easily access relevant information. In one example, the attributes and corresponding attribute values on the object may have a weblink to their respective webpage or data source to indicate the sources from where the attributes and the values are extracted.
[030] Thus, by employing the exemplary system 100, the user can access relevant information in a predefined structure or template known as the object. Also, this information is collated and consolidated from the search results that are extracted from multiple data sources located in unstructured and heterogeneous environment. As result, the user may timely identify the required information without spending much effort and cost on the communication networks or search engines.
[031] Referring to FIG. 2, a detailed block diagram of a system 100 including a processing sub-system 104 communicating with multiple data sources, in accordance with an embodiment of the present subject matter may be described. The processing sub-system 104 is communicatively coupled to an interface unit 102 to receive a search string provided by a user. In one example, the search string may be a text pattern such as, “Image capturing flying object”. The user may enter this search string to obtain relevant information about the devices that are capable of capturing images when the devices are moving at a certain altitude. It may be noted that the above text pattern is used for easy understanding of the invention. The search string may include any text or text pattern and is not limited to the text mentioned above. Further, the processing sub-system 104 is communicatively coupled to a display unit 106 to display search results related to the received search string. Also, the processing sub-system 104 is coupled to the personal data sources and search history 110, the domain specific data sources and domain specific search history 112, and the public and private data sources 114.
[032] The personal data sources and search history 110 may include data related to preferences or pre-stored personalized data of the user. In one example, the personalized data may include a profile of the user, such as name, profession, date/place of birth, social identity, employee identity, interest areas and other similar details of the user. Further, the search history may include information related to search strings, search pattern of the user, frequently and/or recently visited data sources and other similar searched data of the user.
[033] In addition, the personal data sources and search history 110 may include specification templates that are used by the processing sub-system 104 to present the search results to the user. In one example, the specification templates may be a pre-defined structure that is used to show the search results or information extracted from multiple data sources that are located in unstructured and heterogeneous environment.
[034] Further, the personal data sources and search history 110 may include entity-dimensions and attribute dictionary that are used to maintain a list of dimensions for each of the entities and a list of attributes for each of the entity-dimensions. In one example, the entity-dimensions may be defined as the group of co-related attributes of an entity which represents an entity to a defined context (E.g. for an entity ‘Person” may have multiple dimension like “He can be a “Father to somebody”, “Son to somebody”, “colleague to somebody” like different dimension can be there). Similarly, the attribute may be defined as the element which helps to describe dimension of the entity (for example while “employee” may be the dimension of an entity “Person”, there could be different elements like Employee ID, email ID, employer details, experience, salary, position etc. to describe the ‘Employ dimension”. Each one of these ID, email etc. may be attributes). Furthermore, the personal data sources and search history 110 may include attribute pattern definition and attribute value pattern definition that indicate the type of attributes and their corresponding values that need to be selected by the processing sub-system 104. In one example, the user may predefine and store this attribute pattern definition and attribute value pattern definition in the personal data sources and search history 110. Moreover, the personal data sources and search history 110 may be a self-learning part where any new specification, a new template, and/or new attributes will be updated for any future reference.
[035] In a similar manner, the domain specific data sources and domain specific search history 112 may include data related to a domain of the user. This domain may be referred to an area that the user is working or interested. For example, if the user is a gynecologist or pediatrician, the domain of the user may be referred to as a medical domain. Similarly, if the user is a service engineer, the domain of the user may be referred to as a mechanical domain. In one embodiment, the domain specific data sources and domain specific search history 112 may include reference repositories where the information is stored in the format of document, pdf, images, database, etc. Also, this is the second area where the specification, template, and/or attributes related to the entity will be searched. Moreover, this area be referred as a heterogeneous environment local system, FTPs, cloud environment, and/or common repository.
[036] Furthermore, the public and private data sources 114 may include data related to a public or general domain. Data in this area will be available in World Wide Web (WWW), which can be retrieved through web crawler, rest services, web services, etc. This will be the final reference area where the entity, attribute, and attribute values are searched. In one example, public and private data sources 114 may include multiple data sources that are located in an unstructured and heterogeneous environment.
[037] Moreover, for accessing the data from reference repositories in the domain specific data sources and domain specific search history 112 or from the private and public data sources 114, the processing sub-system 104 may use one or more third-party tools, such as web crawler, repository extractor, doc processor, image handler, and OCR handlers. It may be noted that the processing sub-system 104 may use any type of tool or algorithm to extract the data, and is not limited to the tools mentioned above.
[038] As depicted in FIG. 2, the processing sub-system 104 includes an entity identifier 202, a dimension detector 204, and an attribute set creator 206, and an object constructor 208. The entity identifier 202 is coupled to the dimension detector 204 which is in-turn coupled to the attribute set creator 206. Further, the attribute set creator 206 is coupled to the object constructor 208. The entity identifier 202 is configured to receive the search string from the interface unit 102. Based on the received search string, the entity identifier 202 may identify one or more entities that are preferred or likely to be of interest to the user.
[039] In one embodiment, the entity identifier 202 may be referred to as a search engine that is capable of communicating with the multiple data sources to identify the one or more entities. In particular, the entity identifier 202 may search in one or more personal data sources and search history 110 of the user to identify at least one entity preferred by the user. For example, if the search string is “Image capturing flying object”, the entities may be aircrafts, drones, birds, supercharacters (e.g., superman, batman). The entity identifier 202 may search for these entities in the personal data sources and search history 110 of the user. If the at least one entity is not identified in the one or more personal data sources and the search history 110, the entity identifier 202 may search in one or more domain specific data sources and domain specific search history 112 to identify the at least one entity. For example, if the domain of the user is a mechanical domain, the entity identifier 202 may search for entities, such as the aircrafts and the drones in the domain specific data sources and domain specific search history 112. In this example, the entity identifier 202 may ignore the entities such as, birds and human characters as they may be of less likely of interest to the user who is from the mechanical domain.
[040] Further, if the entity identifier 202 fails to identify the at least one entity in the domain specific data sources and domain specific search history 112, the entity identifier 202 may search for the entities in the public and private data sources 114. As these data sources 114 are in unstructured and heterogeneous environment, the entity identifier 202 may search based on the search string of the user. Also, in one embodiment, the entity identifier 202 may use the pre-stored personalized data of the user along with the search string to identify one or more entities that are most likely of interest to the user. It may be noted that the entity identifier 202 may execute one or more ranking algorithms to identify the entities in the personal data sources 110, domain specific data sources 112, or public and private data sources 114. Also, based on the domain and the personalized data of the user, these identified entities are listed and ranked in an order using the ranking algorithms.
[041] Upon identifying the one or more entities, the entity identifier 202 transmits the list of entities to the dimension detector 204. For example, if the search string is “Image capturing flying object”, the entity identifier 202 may identify the entities, such as the Aircrafts, Drones, Birds, and Supercharacters. Further, the dimension detector 204 is configured to determine one or more entity-dimensions for the identified entities based on the received search string. The dimension detector 204 may communicate with the multiple data sources to determine one or more entity-dimensions. In particular, the dimension detector 204 may search in one or more personal data sources and search history 110 of the user to determine the at least one entity-dimension for the identified entity. For example, if the search string is “Image capturing flying object” and the identified entity is “drones”, dimension detector may search for entity-dimensions, such as drone materials, drone components, drone flying manuals, and drone designs.
[042] If the at least one entity-dimension is not determined in the one or more personal data sources and the search history, the dimension detector 204 may search in one or more domain specific data sources and domain specific search history 112. For example, if the domain of the user is a mechanical domain, the dimension detector 204 may search for an entity-dimension, such as the drone components, drone designs, and drone materials in the domain specific data sources and domain specific search history. In this example, the dimension detector 204 may ignore the entity-dimensions such as the drone flying manuals as it may be of less likely of interest to the user who is from the mechanical domain.
[043] Further, if the dimension detector 204 fails to identify the at least one entity-dimension in the domain specific data sources and domain specific search history 112, the dimension detector 204 may search for the entity-dimensions in the public and private data sources 114. As these data sources 114mare in unstructured and heterogeneous environment, the dimension detector 204 may search based on the search string of the user. Also, in one embodiment, the dimension detector 204 may use the pre-stored personalized data of the user along with the search string to identify one or more entity-dimensions that are most likely of interest to the user. It may be noted that the dimension detector 204 may execute one or more accuracy ranking algorithms to identify the entity-dimensions in the personal data sources 110, domain specific data sources 112, or public and private data sources 114. Also, based on the domain and the personalized data of the user, these identified entity-dimensions are listed and ranked in an order using the accuracy ranking algorithms.
[044] After determining the one or more entity-dimensions, the dimension detector 204 transmits the list of dimensions to the attribute set creator 206. For example, if the search string is “Image capturing flying object” and the identified entity is “Drones”, then the determined entity-dimension may be “Drone components”. Further, the attribute set creator 206 is configured to create the attribute set including the attributes and the corresponding attribute values related to the determined at least one entity-dimension based on the search string and the pre-stored personalized data associated with the user. In particular, the attributes and the attribute values of the attribute set may be scattered in different data sources. The attribute set creator 206 is configured to search for these attributes in the multiple data sources specific to the user, the domain of the user, and/or the identified entity that may be preferred or most likely of interest to the user. In one example, the attribute set creator 206 may scrawl for these attributes in the multiple data sources. Thereafter, the attribute set creator 206 may collate and consolidate the attributes and their corresponding attributed values. The multiple data sources may include the private and the public domain sources 114 that are located in unstructured and heterogeneous environment. Also, the multiple data sources may include the search history of the user to provide the personalized data of the user. In one embodiment, the attribute set creator 206 is configured to execute one or more searching algorithms to search the attributes in one or more data sources based on the predefined pattern of the attributes or the attribute pattern definition.
[045] Furthermore, the attribute set creator 206 may group the searched attributes to form the attribute set associated with the determined at least one entity-dimension. The attribute set may include the attributes and the corresponding attribute values referenced to the multiple data sources. In one example, if the determined entity-dimension is “Drone components”, the attributes may be blades, image capturing devices, sensors, processors etc. Similarly, if the attribute “image capturing devices” is ranked at the top in the attribute set, the attribute set creator 206 may search for the attribute values, such as the camera, ultrasound imagers, infrared imagers etc. Further, the attribute set creator 206 may link these attributes and their corresponding attribute values to their respective data sources that are located in unstructured and heterogeneous environment.
[046] In one embodiment, the attribute set creator 206 may include an attribute value conflict handler 216 that is configured to select an attribute value from a plurality of attribute values for each of the attributes. The plurality of attribute values is available in multiple data sources. Also, this attribute value is selected using one or more ranking algorithms. In another embodiment, the attribute set creator 206 may include an attribute value constructor 218 that is configured to construct an attribute value by combining different parts of the attribute value. The different parts of the attribute value may be available in multiple data sources.
[047] In addition, the attribute set creator 206 may include an attribute value ranking unit 220 that is used to rank the attribute values in a particular order. Also, the attribute set creator 206 may include an attribute value duplicate eliminator 222 that is used to remove repeated attribute values that are collated from different data sources. Further, the attribute set creator 206 may include an attribute value association unit 224 that is used for associating attribute values to their respective attributes. Furthermore, the attribute set creator 206 may include an attribute value collection unit 226 that is used for collecting the attribute values from different multiple data sources. Additionally, the attribute set creator 206 may include an attribute identification unit 228 that is used for identifying the attributes in different multiple data sources.
[048] Upon creating the attribute set, the attribute set creator 206 may transmit the attribute set to the object constructor 208 that is configured to construct the object in a predefined template using the attribute set having the attributes and the corresponding attribute values referenced to the multiple data sources. In one embodiment, the object constructor 208 may select one of the specification templates stored in the personal data sources and search history 110. Further, the object constructor 208 may construct the object having the attributes and the corresponding attribute values using the selected specification template.
[049] In some embodiments, the processing sub-system 104 may be configured to communicate any new object, new attribute set, new attributes and new attribute values, new entity, and/or new entity-dimension to the personal data sources and search history 110 to update the personal data sources and search history 110. In one example, if the processing sub-system 104 determines a new specification template and/or new specification/object, the processing sub-system 104 updates the new specification template in the specification templates using a specification template updater 230 and the specification history using the specification history updater 232.
[050] Similarly, the processing sub-system 104 may update a new attribute in the attribute dictionary using an entity type attribute dictionary updater 234. Also, the processing sub-system 104 may update a new attribute pattern definition or a new attribute value definition using an attribute pattern definition updater 236 and an attribute value pattern definition updater 238.
[051] Upon constructing the object including the attribute set having the attributes and the corresponding attribute values, the processing sub-system 204 may display the constructed object on the display unit 106 so that the user can easily access relevant information. The object may be displayed in the predefined template or structure with the attributes and their attribute values linked or referenced with multiple date sources. These multiple data sources may be located in unstructured and heterogeneous environment. In one embodiment, the object constructor 208 may construct different objects and may display these objects in the display unit 106, as depicted in FIG. 2.
[052] Referring to FIG. 3, a flow chart illustrating a method 300 for creating the attribute set with associated attribute values for the search string of the user may be described. For ease of understanding, the method 300 is described with reference to the components shown in FIGs. 1 and 2. The method 300 begins with a step of 302, where the interface unit receives a search string of a user. In one example, the search string may be a text pattern.
[053] Subsequently, at step 304, the processing sub-system may create an attribute set including one or more of attributes and corresponding attribute values based on the received search string and pre-stored personalized data of the user. The attributes and the corresponding attribute values may be extracted from multiple data sources located in unstructured and heterogeneous environment. In particular, the processing sub-system may identify at least one entity that is related to the search string based on the search string and personalized data of the user. Further, the processing sub-system may determine at least one entity-dimensions that are related to the identified entity. Thereafter, the processing sub-system may create an attribute set having the attributes and corresponding attribute values related to the determined at least one entity-dimension. Finally, the processing sub-system may construct the object using the created attribute set in a predefined template.
[054] In addition, at step 306, the processing sub-system may display the object including the attribute set having the attributes and the corresponding attribute values referenced to the multiple data sources. This in-turn substantially reduces the time, cost, and effort of the user for accessing the relevant information.
[055] Exemplary embodiments discussed above may provide certain advantages. Though not required to practice aspects of the disclosure, these advantages may include easy access of the information in a predefined structure or template known as the object. This aid in quicker searching of information. Also, this information is collated and consolidated from the search results that are extracted from multiple data sources located in unstructured and heterogeneous environment. As result, the user may timely identify the required information without spending much time, effort, and cost on the communication networks or search engines.

Claims:
1. A system comprising:
an interface unit configured to receive a search string of a user;
a processing sub-system communicatively coupled to the interface unit and configured to create an attribute set comprising a plurality of attributes and corresponding attribute values based on the received search string and pre-stored personalized data of the user, wherein the attributes and the corresponding attribute values are extracted from multiple data sources located in unstructured and heterogeneous environment; and
a display unit electrically coupled to the processing sub-system and configured to display an object comprising the attribute set having the attributes and the corresponding attribute values referenced to the multiple data sources.

2. The system of claim 1, wherein the processing sub-system comprises:
an entity identifier configured to identify at least one entity preferred by the user based on the received search string;
a dimension detector communicatively coupled to the entity identifier and configured to determine at least one entity-dimension for the identified at least one entity based on the received search string; and
an attribute set creator communicatively coupled to the dimension detector and configured to create the attribute set comprising the attributes and the corresponding attribute values related to the determined at least one entity-dimension based on the search string and the pre-stored personalized data associated with the user.

3. The system of claim 2, wherein the entity identifier is configured to:
search in one or more personal data sources and search history of the user to identify the at least one entity preferred by the user;
search in one or more domain specific data sources and domain specific search history to identify the at least one entity if the at least one entity is not identified in the one or more personal data sources and the search history; and
search in one or more public and private data sources based on the search string to identify the at least one entity if the at least one entity is not identified in the domal specific data sources and the domain specific search history.

4. The system of claim 3, wherein the entity identifier is configured to execute one or more ranking algorithms to identify the at least one entity preferred by the user.

5. The system of claim 2, wherein the dimension detector is configured to:
search in one or more personal data sources and search history of the user to determine the at least one entity-dimension for the identified at least one entity;
search in one or more domain specific data sources and domain specific search history to determine the at least one entity-dimension for the identified at least one entity if the at least one entity-dimension is not determined in the one or more personal data sources and the search history; and
search in one or more public and private data sources based on the search string to determine the at least one entity-dimension for the identified at least one entity if the at least one entity-dimension is not determined in the one or more domal specific data sources and the domain specific search history.

6. The system of claim 5, wherein the dimension detector is configured to execute one or more accuracy ranking algorithms to determine the at least one entity-dimension for the identified at least one entity.
7. The system of claim 2, wherein the attribute set creator is configured to:
search for the attributes in multiple data sources specific to at least one of the user, a domain of the user, and the identified at least one entity preferred by the user, wherein the multiple data sources comprise a private data source, a public domain source, and search history of the user, wherein the multiple data sources are located in unstructured and heterogeneous environment; and
group the searched attributes to form the attribute set associated with the determined at least one entity-dimension, wherein the attribute set comprises the attributes and the corresponding attribute values referenced to the multiple data sources.

8. The system of claim 7, wherein the attribute set creator is configured to execute one or more searching algorithms to search the attributes in one or more data sources based on a predefined pattern of the attributes.

9. The system of claim 7, wherein the attribute set creator comprises an attribute value conflict handler configured to select an attribute value from a plurality of attribute values for each of the attributes, wherein the plurality of attribute values is available in multiple data sources, and wherein the attribute value is selected using one or more ranking algorithms.

10. The system of claim 7, wherein the attribute set creator comprises an attribute value constructor configured to construct an attribute value by combining different parts of the attribute value, wherein the different parts of the attribute value are available in multiple data sources.

11. The system of claim 7, wherein the processing sub-system further comprises an object constructor communicatively coupled to the attribute set creator and configured to construct the object in a predefined template using the attribute set having the attributes and the corresponding attribute values referenced to the multiple data sources.

12. The system of claim 11, wherein the processing sub-system is configured to communicate at least one of the object, the attribute set, the attributes and the attribute values, the entity, and the entity-dimension to one or more personal data sources and search history of the user to update the one or more personal data sources and search history.

13. A method comprising:
receiving, by an interface unit, a search string of a user;
creating, by a processing sub-system, an attribute set comprising a plurality of attributes and corresponding attribute values based on the received search string and pre-stored personalized data of the user, wherein the attributes and the corresponding attribute values are extracted from multiple data sources located in unstructured and heterogeneous environment; and
displaying, by a display unit, an object comprising the attribute set having the attributes and the corresponding attribute values referenced to the multiple data sources.

14. The method of claim 13, wherein creating, by the processing sub-system, the attribute set comprises:
identifying, by an entity identifier of the processing sub-system, at least one entity preferred by the user based on the received search string;
determining, by a dimension detector of the processing sub-system, at least one entity-dimension for the identified at least one entity based on the received search string; and
creating, by an attribute set creator of the processing sub-system, the attribute set comprising the attributes and corresponding attribute values related to the determined at least one entity-dimension based on the search string and the pre-stored personalized data associated with the user.

15. The method of claim 14, wherein identifying, by the entity identifier of the processing sub-system, the at least one entity comprises:
searching in one or more personal data sources and search history of the user to identify the at least one entity preferred by the user;
searching in one or more domal specific data sources and domain specific search history to identify the at least one entity if the at least one entity is not identified in the one or more personal data sources and the search history; and
searching in one or more public and private data sources based on the search string to identify the at least one entity if the at least one entity is not identified in the domal specific data sources and the domain specific search history.

16. The method of claim 14, wherein determining, by the dimension detector of the processing sub-system, the at least one entity-dimension comprises:
searching in one or more personal data sources and search history of the user to determine the at least one entity-dimension for the identified at least one entity;
searching in one or more domal specific data sources and domain specific search history to determine the at least one entity-dimension for the identified at least one entity if the at least one entity-dimension is not determined in the one or more personal data sources and the search history; and
searching in one or more public and private data sources based on the search string to determine the at least one entity-dimension for the identified at least one entity if the at least one entity-dimension is not determined in the one or more domal specific data sources and the domain specific search history.

17. The method of claim 14, wherein creating, by the attribute set creator of the processing sub-system, the attribute set comprises:
searching for the attributes in multiple data sources specific to at least one of the user, a domain of the user, and the identified at least one entity preferred by the user, wherein the multiple data sources comprise a private data source, a public domain source, and search history of the user, wherein the multiple data sources are located in unstructured and heterogeneous environment; and
grouping the searched attributes to form the attribute set associated with the determined at least one entity-dimension, wherein the attribute set comprises the attributes and the corresponding attribute values referenced to the multiple data sources.

18. The method of claim 14, wherein creating, by the attribute set creator of the processing sub-system, the attribute set comprises selecting, by an attribute value conflict handler, an attribute value from a plurality of attribute values for each of the attributes, wherein the plurality of attribute values is available in multiple data sources, and wherein the attribute value is selected using one or more ranking algorithms.

19. The method of claim 14, wherein creating, by the attribute set creator of the processing sub-system, the attribute set comprises constructing, by an attribute value constructor, an attribute value by combining different parts of the attribute value, wherein the different parts of the attribute value are available in multiple data sources.

20. The method of claim 13, wherein creating, by the processing sub-system, the attribute set comprises constructing, by an object constructor of the processing sub-system, the object in a predefined template using the attribute set having the attributes and the corresponding attribute values referenced to the multiple data sources.

21. A non-transitory computer-readable medium storing instructions executable by a processing system to perform a method, the method comprising:
receiving a search string of a user;
creating an attribute set comprising a plurality of attributes and corresponding attribute values based on the received search string and pre-stored personalized data of the user, wherein the attributes and the corresponding attribute values are extracted from multiple data sources located in unstructured and heterogeneous environment; and
displaying an object comprising the attribute set having the attributes and the corresponding attribute values referenced to the multiple data sources.