USER ROLE BASED CUSTOMIZABLE SEMANTIC SEARCH
BACKGROUND
[0001] Search engines discover and store information about documents such as web
pages, which they typically retrieve from the textual content of the documents. The
documents are sometimes retrieved by a crawler or an automated browser, which may
follow links in a document or on a website. Conventional crawlers typically analyze
documents as flat text files examining words and their positions (e.g. titles, headings, or
special fields). Data about analyzed documents may be stored in an index database for use
in later queries. A query may include a single word or a combination of words.
[0002] Usefulness of a search engine depends on the relevance of the result set it
returns. While there may be a large number of documents that include a particular word or
phrase, some pages may be more relevant, popular, or authoritative than others. Thus,
many search engines employ a variety of methods to rank the results. Some search
engines utilize predefined and/or hierarchically ordered keywords that have been preprogrammed.
Other search engines generate the index by analyzing located texts
automatically.
[0003] Some aspects of search that is typically not taken into account by
conventional search engines is that same words may have different meanings to different
users. Moreover, the same document may be more important to a group of people and less
important to another group of people based on the contained information. Furthermore,
different contents of a document such as images, graphics, or text may influence an
importance of the document to different users. Thus, flat text based searches fail to
consider a significant portion of information regarding available documents when ranking
documents.
SUMMARY
[0004] This summary is provided to introduce a selection of concepts in a simplified
form that are further described below in the Detailed Description. This summary is not
intended to exclusively identify key features or essential features of the claimed subject
matter, nor is it intended as an aid in determining the scope of the claimed subject matter.
[0005] Embodiments are directed to user role based customizable searches, where
crawled documents may be evaluated against user roles or attributes. According to some
embodiments, metadata retrieved from searched documents may also be evaluated against
the user roles and/or attributes such that customized search results ranking documents
based on their content beyond textual content may be provided.
[0006] These and other features and advantages will be apparent from a reading of
the following detailed description and a review of the associated drawings. It is to be
understood that both the foregoing general description and the following detailed
description are explanatory and do not restrict aspects as claimed.
BRIEF DESCRIPTION OF THE DRAWINGS
[0007] FIG. 1 is a diagram illustrating use of different user roles in performing
searches across various sources;
[0008] FIG. 2 is a conceptual diagram illustrating user role based search operations
in a desktop search environment;
[0009] FIG. 3 is a conceptual diagram illustrating user role based search operations
in a networked search environment;
[0010] FIG. 4 illustrates examples of how a user role based search may focus on
different contents of a document in a system according to embodiments;
[0011] FIG. 5 is a networked environment, where a system according to
embodiments may be implemented;
[0012] FIG. 6 is a block diagram of an example computing operating environment,
where embodiments may be implemented; and
[0013] FIG. 7 illustrates a logic flow diagram for a process of performing user role
based customizable search according to embodiments.
DETAILED DESCRIPTION
[0014] As briefly described above, user roles such as organizational hierarchy,
membership in an organization, attributes, etc., may be determined and used in performing
customizable searches evaluating crawled documents against user roles or attributes.
Moreover, metadata retrieved from searched documents may also be evaluated against the
user roles and/or attributes such that customized search results may be ranked accordingly.
Thus, a search engine/application according to embodiments performs a semantic search
deriving meaning from searched content, metadata, user role(s), predefined rules, etc. In
the following detailed description, references are made to the accompanying drawings that
form a part hereof, and in which are shown by way of illustrations specific embodiments
or examples. These aspects may be combined, other aspects may be utilized, and
structural changes may be made without departing from the spirit or scope of the present
disclosure. The following detailed description is therefore not to be taken in a limiting
sense, and the scope of the present invention is defined by the appended claims and their
equivalents.
[0015] While the embodiments will be described in the general context of program
modules that execute in conjunction with an application program that runs on an operating
system on a personal computer, those skilled in the art will recognize that aspects may also
be implemented in combination with other program modules.
[0016] Generally, program modules include routines, programs, components, data
structures, and other types of structures that perform particular tasks or implement
particular abstract data types. Moreover, those skilled in the art will appreciate that
embodiments may be practiced with other computer system configurations, including
hand-held devices, multiprocessor systems, microprocessor-based or programmable
consumer electronics, minicomputers, mainframe computers, and comparable computing
devices. Embodiments may also be practiced in distributed computing environments
where tasks are performed by remote processing devices that are linked through a
communications network. In a distributed computing environment, program modules may
be located in both local and remote memory storage devices.
[0017] Embodiments may be implemented as a computer-implemented process
(method), a computing system, or as an article of manufacture, such as a computer
program product or computer readable media. The computer program product may be a
computer storage medium readable by a computer system and encoding a computer
program that comprises instructions for causing a computer or computing system to
perform example process(es). The computer-readable storage medium can for example be
implemented via one or more of a volatile computer memory, a non-volatile memory, a
hard drive, a flash drive, a floppy disk, or a compact disk, and comparable media.
[0018] Throughout this specification, the term "platform" may be a combination of
software and hardware components for managing computer and network operations, which
may include searches. Examples of platforms include, but are not limited to, a hosted
service executed over a plurality of servers, an application executed on a single server, and
comparable systems. The term "server" generally refers to a computing device executing
one or more software programs typically in a networked environment. However, a server
may also be implemented as a virtual server (software programs) executed on one or more
computing devices viewed as a server on the network. More detail on these technologies
and example operations is provided below.
[0019] FIG. 1 is a diagram illustrating use of different user roles in performing
searches across various sources. One measure for the quality of a search engine is the
relevance of the result set it returns. As mentioned previously, search engines employ a
variety of methods to rank the results or index them based on relevance, popularity, or
authoritativeness of documents compared to others. Indexing also allows users to find
sought information promptly.
[0020] When a user submits a query to a search engine (e.g. by using key words), the
search engine may examine its index and provide a listing of matching results according to
predefined criteria. The index may be built from the information stored with the crawled
document and/or user data and the method by which the information is indexed. The
query may include parameters such as Boolean operators (e.g. AND, OR, NOT, etc.) that
allow the user to refine and extend the terms of the search.
[0021] A search engine according to embodiments enables enhanced indexing of
search results by taking user roles / attributes into account. As shown in diagram 100,
different users may have varying roles or attributes within an organization such as user
roles 102, 104, and 106. For example, a document may include data portions of which are
of interest to different people. A teacher may be interested in grades of his/her class for a
particular year, while a principal is interested in overall grade point averages and a
counselor is interested in progress reports. Thus, the same grade report document for a
school may carry different weights for different people. Following the same example,
grades may be stored in different documents all named grade reports. Reporting the
individual grades document to the principal may unnecessarily clutter the principal's
search results and vice versa. Moreover, even if all the data are stored in one document, a
search engine according to embodiments may render different descriptions of the
document to different users based on their interests (rules).
[0022] Thus, search engine 108 according to some embodiments may take the roles
of the users into account and rank the documents accordingly employing customizable
rules defined to evaluate the importance of a document for a specific user role as described
in more detail below. The user roles may be based on organizational hierarchies within an
enterprise and/or attributes of users based on their profession, age, social status,
membership or hierarchy in an organization (e.g. a social network), gender, etc. Roles are
not limited to these example ones and may include any attribute such as a hobby, a
subscription to a particular publication, and similar ones.
[0023] The users' attributes may define different meanings for words being used as
search term. For example, a doctor may mean something different when they search for
test compared to a student. Similarly, credentials of a user such as their permission levels
may be used by search engine as well. A manager within an organization may have
different permission levels compared to a sales representative. Thus, documents with
content not accessible to the sale representative may be de-prioritizes in a search, while
documents with restricted access may be determined to be more relevant for the manager.
[0024] Customizable business rules may also define different groups of metadata.
For example, data source, data type, content distribution, and similar attributes associated
with searched documents may be used to further enhance ranking of search results.
Moreover, rules may define importance of a metadata group for specific user roles. For
example, documents may be tagged as sales summary report or as forecast reports. These
document metadata may help prioritize the document(s) differently for sales managers or
marketing managers in addition to the documents' contents.
[0025] In addition to employing customizable evaluation rules based on user roles
and metadata, customizable rendering rules may also be utilized to render the search
results based on the importance of the content and metadata of the documents. Thus,
search engine 108 may perform the search(es) utilizing the customizable rules passing
them as query parameters at crawl time on data sources 110, which may include database
server 112, analysis services 118, portals 114 (e.g. web share services), desktop 116, and
other data sources 120.
[0026] FIG. 2 is a conceptual diagram illustrating user role based search operations
in a desktop search environment. Search operations may be performed in different
environments. One example environment, user's desktop is shown in diagram 200.
[0027] User 222 may execute a number of applications 228 in their computing
device 224. Some of the applications may be executed locally, while other may be
distributed applications executed on other computing devices and accessed through
computing device 224. Data 230 may be any data generated and/or consumed by
applications 228 or other wide stored in computing device 224.
[0028] Search engine 208 may receive user information 232 such as user roles,
attributes, permissions, and similar credentials and determine customizable rules for
evaluating documents. The roles may be determined through lookup (e.g. looking up a
table of user credentials and corresponding roles, etc.), inference (e.g. an automatic
inference algorithm inferring a user role based on the user's email address, etc.),
predefined rules defining user roles, or similar methods. User credentials or identities may
be received by the search engine 208 through a user interface input (e.g. log in) or through
the operating system and/or another application. The rules, as mentioned above, may be
predefined (e.g. by an administrator) or dynamically determined based on user roles and
search terms by a search application. For example, a search for "music" may not take into
account a user's organizational position, but his/her age, membership in a social network,
language preferences, and similar attributes. Search results indexed based on evaluating
document contents and metadata may be provided to rendering application 226, which
may use additional customizable rules based on user roles to rank rendering of documents
and associated metadata before rendering the search results to user 222.
[0029] FIG. 3 is a conceptual diagram illustrating user role based search operations
in a networked search environment. The networked search environment shown in diagram
300 is for illustration purposes. Embodiments may be implemented in various networked
environments such as enterprise-based networks, cloud-based networks, and combinations
of those.
[0030] User 322 may interact with a variety of networked services through their
client 324. Client 324 may refer to a computing device executing one or more
applications, an application executed on one or more computing devices, or a service
executed in a distributed manner and accessed by user 322 through a computing device.
In a typical system client 324 may communicate with one or more servers (e.g., server
332). Server 332 may execute search operations for user 322 searching documents on
server 332 itself, other clients 334, data stores 336, other servers of network 338, or
resources outside network 330.
[0031] In an example scenario, network 330 may represent an enterprise network,
where user 322 may provide their credentials to login (e.g. a user name, a password, an
email address, and the like). Based on the provided credentials, the search application on
server 332 may determine customizable rules based on user roles (e.g. enterprise roles)
and evaluate documents and associated metadata. The search may also include resources
outside network 330 such as server 342 or servers 346 and data stores 344, which may be
accessed through at least one other network 340.
[0032] As discussed above, user 322 may provide a credential (e.g. a login,
username/password, a certificate, a personal identification number, and comparable ones)
for accessing network 330 that includes server 332 executing the search application. User
322 may have multiple identities associated with different services. These sub-identities
may be determined from the provided credential through a look-up operation, by inferring
from user credentials (e.g. user email address), or by executing an algorithm that, for
example, may derive a number of user identities from an encrypted user credential through
decryption. Once the sub-identities are determined, user's (322) roles may be determined
based on enterprise rules, associations, personal information, and comparable data.
[0033] According to other embodiments, user 322 may provide at least some of the
sub-identities directly through a credential input user interface (e.g. entry of user name).
The determination of the user roles may be performed on-demand (user indication),
randomly, or periodically. Determined user roles may be cached or persistently stored for
subsequent use. The determination schedule, whether or not the determined roles are to be
cached, and associated determination mechanisms may be established based on the
individual sub-identities.
[0034] The user role provision and determination methods discussed above are
example methods provided for illustrative purposes and do not constitute a limitation on
embodiments. User role(s) for enhancing search operations may be determined in a
variety of ways such as look-up operations, automated inference, and the like, using the
principles described herein.
[0035] Thus, in a system according to embodiments, documents may be evaluated
determining the importance of each document based on various user role based rules.
Metadata from the documents may also be grouped and each metadata group evaluated
based on the user roles. Documents whose content and/or metadata are deemed to be
more important for a particular user may be ranked higher. Each group of metadata may
also be customized for each user role for rendering purposes.
[0036] The example systems in FIG. 1, 2, and 3 have been described with specific
servers, client devices, software modules, and interactions. Embodiments are not limited
to systems according to these example configurations. A user role based customizable
search system may be implemented in configurations employing fewer or additional
components and performing other tasks. Furthermore, specific protocols and/or interfaces
may be implemented in a similar manner using the principles described herein.
[0037] FIG. 4 illustrates examples of how a user role based search may focus on
different contents of a document in a system according to embodiments. While
embodiments may be implemented on any document type, two example documents are
illustrated in FIG. 4.
[0038] Document 450 is an example spreadsheet document. Document 450 includes
sales related information for a company. Portions of the data in the document 450 may be
relevant to different people, or even restricted for display depending on different users'
permission levels. For example, North America Sales data 452 may be relevant to a sales
representative, while Forecasts 454 may be relevant to a marketing person. Similarly,
profit reports 456 may be relevant to an executive. Thus, a search according to some
embodiments may retrieve the entire document or portions of it depending on the user's
role or attribute.
[0039] Document 460 may be a word processing document with textual and
graphical elements. According to an example scenario, a child searching for animal
stories may be more interested in the graphics 466 and 468 of document 460. An adult
searching for stories may find the textual part 465 more relevant. Similarly, a teenager
may be more interested in characters in a story and the character names 462 and 464 may
be relevant for that particular user. In addition to the illustrated content types, which may
be evaluated against user roles and attributes by a search engine according to
embodiments, metadata associated with the document 460 such as tags assigned to the
document indicating document type, assigned keywords, etc. or creation date may also be
evaluated against user roles.
[0040] FIG. 5 is an example networked environment, where embodiments may be
implemented. A platform providing user role based customizable searches may be
implemented via software executed over one or more servers 514 such as a hosted service.
The platform may communicate with client applications on individual computing devices
such as a smart phone 513, a laptop computer 51 , or desktop computer 5 11 ('client
devices') through network(s) 510.
[0041] As discussed above, client applications executed on any of the client devices
5 11-513 may submit a search request to a search engine on the client device 511-5 13, on
the servers 514, or on individual server 516. The search engine may determine any
relevant user roles such as enterprise attributes, social networking attributes, permission
levels, and comparable ones for the user submitting the request. The search engine may
then perform the search ranking documents considering the user roles as discussed
previously. The service may retrieve relevant data from data store(s) 519 directly or
through database server 518, and provide the ranked search results to the user(s) through
client devices 511-513.
[0042] Network(s) 510 may comprise any topology of servers, clients, Internet
service providers, and communication media. A system according to embodiments may
have a static or dynamic topology. Network(s) 510 may include secure networks such as
an enterprise network, an unsecure network such as a wireless open network, or the
Internet. Network(s) 510 may also coordinate communication over other networks such as
Public Switched Telephone Network (PSTN) or cellular networks. Furthermore,
network(s) 510 may include short range wireless networks such as Bluetooth or similar
ones. Network(s) 510 provide communication between the nodes described herein. By
way of example, and not limitation, network(s) 510 may include wireless media such as
acoustic, RF, infrared and other wireless media.
[0043] Many other configurations of computing devices, applications, data sources,
and data distribution systems may be employed to implement a framework for user role
based customizable search. Furthermore, the networked environments discussed in FIG. 5
are for illustration purposes only. Embodiments are not limited to the example
applications, modules, or processes.
[0044] FIG. 6 and the associated discussion are intended to provide a brief, general
description of a suitable computing environment in which embodiments may be
implemented. With reference to FIG. 6, a block diagram of an example computing
operating environment for an application according to embodiments is illustrated, such as
computing device 600. In a basic configuration, computing device 600 may be a client
device executing a client application capable of performing searches or a server executing
a service capable of performing searches according to embodiments and include at least
one processing unit 602 and system memory 604. Computing device 600 may also
include a plurality of processing units that cooperate in executing programs. Depending
on the exact configuration and type of computing device, the system memory 604 may be
volatile (such as RAM), non-volatile (such as ROM, flash memory, etc.) or some
combination of the two. System memory 604 typically includes an operating system 605
suitable for controlling the operation of the platform, such as the WINDOWS ® operating
systems from MICROSOFT CORPORATION of Redmond, Washington. The system
memory 604 may also include one or more software applications such as program modules
606, search capable application 622, search engine 624, and optionally other
applications/data 626.
[0045] Application 622 may be any application that is capable of performing search
through search engine 624 on other applications / data 626 in computing device 600 and/or
on various kinds of data available in an enterprise-based or cloud-based networked
environment. Search engine 624 may determine user role(s) and attribute(s), and
customize searches and rank results taking those roles and attributes into account as
discussed previously. Application 622 and search engine 624 may be separate
applications or an integral component of a hosted service. This basic configuration is
illustrated in FIG. 6 by those components within dashed line 608.
[0046] Computing device 600 may have additional features or functionality. For
example, the computing device 600 may also include additional data storage devices
(removable and/or non-removable) such as, for example, magnetic disks, optical disks, or
tape. Such additional storage is illustrated in FIG. 6 by removable storage 609 and non
removable storage 610. Computer readable storage media may include volatile and
nonvolatile, removable and non-removable media implemented in any method or
technology for storage of information, such as computer readable instructions, data
structures, program modules, or other data. System memory 604, removable storage 609
and non-removable storage 610 are all examples of computer readable storage media.
Computer readable storage media includes, but is not limited to, RAM, ROM, EEPROM,
flash memory or other memory technology, CD-ROM, digital versatile disks (DVD) or
other optical storage, magnetic tape, magnetic disk storage or other magnetic storage
devices, or any other medium which can be used to store the desired information and
which can be accessed by computing device 600. Any such computer readable storage
media may be part of computing device 600. Computing device 600 may also have input
device(s) 612 such as keyboard, mouse, pen, voice input device, touch input device, and
comparable input devices. Output device(s) 614 such as a display, speakers, printer, and
other types of output devices may also be included. These devices are well known in the
art and need not be discussed at length here.
[0047] Computing device 600 may also contain communication connections 616 that
allow the device to communicate with other devices 618, such as over a wired or wireless
network in a distributed computing environment, a satellite link, a cellular link, a short
range network, and comparable mechanisms. Other devices 618 may include computer
device(s) that execute communication applications, other web servers, and comparable
devices. Communication connection(s) 616 is one example of communication media.
Communication media can include therein computer readable instructions, data structures,
program modules, or other data. By way of example, and not limitation, communication
media includes wired media such as a wired network or direct-wired connection, and
wireless media such as acoustic, RF, infrared and other wireless media.
[0048] Example embodiments also include methods. These methods can be
implemented in any number of ways, including the structures described in this document.
One such way is by machine operations, of devices of the type described in this document.
[0049] Another optional way is for one or more of the individual operations of the
methods to be performed in conjunction with one or more human operators performing
some. These human operators need not be collocated with each other, but each can be
only with a machine that performs a portion of the program.
[0050] FIG. 7 illustrates a logic flow diagram for a process 700 of performing user
role based customizable search according to embodiments. Process 700 may be
implemented as part of an application executed on a server or client device.
[0051] Process 700 begins with operation 710, where searched contents are crawled.
During crawl time special handling is performed, for example, using security credential or
adding metadata for each user. At operation 720, user group information is retrieved (e.g.
based on user credentials). This may be followed by operation 730, where search results
are indexed (for fast retrieval of information). At operation 740, a search request is
received from a user. At subsequent operation 750 one or more user roles may be
determined based on the retrieved user group specific information. The user roles may
include any attribute, permission, credential associated with the user submitting the search
request. The roles may be determined through lookup (e.g. looking up a table of user
credentials and corresponding roles, etc.), inference (e.g. an automatic inference algorithm
inferring a user role based on the user's email address, etc.), predefined rules defining user
roles, or similar methods. According to some embodiments, the user roles may already be
determined prior to receiving the search request.
[0052] At operation 760, applicable rules may be determined. The rules may be
predefined by a user or administrator, automatically defined/adjusted based on system
parameters and/or user role(s) determined at operation 750. The applicable rules are
defined to evaluate the importance of contents of a document and metadata associated with
the document for specific user role(s). At operation 770, the search may be performed
employing the rules and evaluating ranking of documents at query time. Searched
document contents may include textual data, graphical data, video data, embedded content,
characters, and comparable content. According to other embodiments, user role(s) may be
passed as a query parameter. At operation 780, different groups of metadata associated
with discovered documents may be sorted based on their importance with regard to the
user role(s) and included in the ranked results, which are returned to the requesting
application at operation 790.
[0053] The operations included in process 700 are for illustration purposes. User
role based customizable search may be implemented by similar processes with fewer or
additional steps, as well as in different order of operations using the principles described
herein.
[0054] The above specification, examples and data provide a complete description of
the manufacture and use of the composition of the embodiments. Although the subject
matter has been described in language specific to structural features and/or methodological
acts, it is to be understood that the subject matter defined in the appended claims is not
necessarily limited to the specific features or acts described above. Rather, the specific
features and acts described above are disclosed as example forms of implementing the
claims and embodiments.
CLAIMS
WHAT IS CLAIMED IS:
1. A method to be executed at least in part in a computing device for
performing user role based customizable searches, the method comprising:
crawling searched contents;
retrieving user group specific information;
indexing search results based on the user group specific information;
receiving a search request from a user;
determining a user role for the user;
determining at least one applicable rule for evaluating document content
relevance based on the user role;
ranking the search results taking into consideration the user role; and
rendering the search results.
2. The method of claim 1, further comprising:
determining at least one other applicable rule for evaluating document
metadata relevance based on the user role; and
evaluating the documents based on the at least one other rule.
3. The method of claim 1, further comprising:
determining at least one further applicable rule for rendering documents
based on metadata relevance to the user role; and
rendering the search results based on the at least one further rule.
4. The method of claim 1, wherein the user role is determined based on at
least one from a set of: an organizational hierarchy, a profession, an age, a social status, a
membership in an organization, and a gender of the user.
5. The method of claim 1, wherein the search is performed in one of a desktop
environment and a networked environment.
6. The method of claim 1, wherein the user role is determined in response to
one of: expiration of a predefined period, expiration of a random period, and a user
indication.
7. The method of claim 1, wherein the document content includes at least one
from a set of: textual data, graphical data, video data, embedded content, and characters.
8. A server for facilitating user role based customizable searches in a
networked system, the server comprising:
a memory;
a processor coupled to the memory, the processor executing a search
application in conjunction with instructions stored in the memory, wherein the search
application is configured to:
receive a user credential and a search request associated with a user;
crawl searched contents;
retrieve user group specific information based on the user
credential;
index search results based on the user group specific information;
determine at least one user role for the user based on the user group
specific information;
determine applicable rules for evaluating document content
relevance and evaluating document metadata relevance based on the user role;
evaluate documents based on the applicable rules;
rank the search results;
determine an applicable rule for rendering documents based on
metadata relevance to the user role; and
provide the ranked search results ranked according to the rule for
rendering the documents to a client application.
9. The server of claim 8, wherein documents deemed to be relevant to the user
based on at least one of document content and document metadata are ranked higher in the
rendered search results.
10. The server of claim 8, wherein the user role is determined in one of a
random, periodic, and on-demand manner, and the determined user role is stored for
subsequent use.
11. The server of claim 8, wherein the user role is determined based on at least
one from a set of: a system rule, a user association, and user personal information.
1 . The server of claim 8, wherein the search is performed on at least one from
a set of: a database source, an analysis service, a portal, another server, and a desktop .
13. A computer-readable storage medium with instructions stored thereon for
performing user role based customizable searches, the instructions comprising:
crawling searched contents;
retrieving user group specific information;
indexing search results based on the user group specific information;
receiving a search request from a user;
determining a plurality of user roles based on at least one from a set of: a
system rule, a user association, user group specific information, and user personal
information;
evaluating documents based on their content and the user roles;
grouping metadata associated with documents and evaluating each
metadata group based on the user roles;
ranking documents based on the evaluations; and
rendering search results comprising the ranked documents and the
associated metadata.
14. The computer-readable medium of claim 13, wherein the instructions
further comprise:
customizing each group of metadata based on the user roles for rendering
the search results.
15. The computer-readable medium of claim 13, wherein performing the search
includes executing a query and passing customizable rules based on user roles for
evaluating the documents and the metadata groups as query parameters.