Description:TECHNICAL FIELD
The present invention generally relates to social computing and live-social interaction, and more particularly to a novel method and a novel system for identifying selective information during the live-social interaction under a module of live-integrative online shopping.
BACKGROUND
Historically, shopping is an activity that has involved a customer visiting a number of retail stores, browsing through inventory, selecting products of interest, and checking out to complete a purchase. Also, mail order companies introduced catalogue-based shopping, whereby a customer peruses a printed catalogue, views a catalogue listing, and then places an order for a product via letter or telephone. The ordered product is delivered to the customer's premise a few days later. Although convenient, catalogue-based shopping has inherent disadvantages, such as a lack of photo views of a product. High printing costs limited the number of photos of a product, particularly with respect to different angles or product variations.
Additionally, in late 20th century home shopping channels on cable television were introduced. The home shopping channels offered television programming that described products for sale that could be ordered by phone. Viewers would regularly tune-in to see products that were displayed and talked about by live hosts. Enthusiastic personalities often developed a loyal following, and the shopping channels would give many hosts creative freedom in merchandising products.
Moreover, in recent years, a wealth of opportunities for sales-based innovations have arisen with the continued growth in popularity of online shopping. Within the World Wide Web (WWW) and the Internet, users can access an infinite source of sites, including social media sites where live streaming events are used for entertainment and marketing products directly to targeted consumer groups.
The online retailers and home shopping television channels may lack the human component that motivates people to purchase. For example, a person may create a video showing others how to use a particular product. During the video, the person may express opinions regarding the product. Viewers may then be motivated to purchase the product after viewing the video. However, this do not provide chance to a buyer/consumer to interact with the seller and get a chance to proceed with the shopping under his/her terms. On other hand, in recent pandemic situations, the conventional shopping activity that has involved a customer visiting a number of retail stores involves a risk of spreading infection, despite of having human touch in shopping.
Despite advancements that have been made in the aforementioned shopping methods, there exists a need to design a shopping system which eliminates chances of spreading the infection and providing human touch in online shopping.
SUMMARY
An object of the present invention is to provide an easy-to-use system and a method for identifying selective information during the live-integrative online shopping which enhances the buyers experience and eases the process item selection in online shopping.
In one aspect, an embodiment of the present disclosure provides a system for identifying selective information, wherein the system comprises:
- a plurality of terminal devices, wherein the plurality of terminal devices comprises at least one user interface; and
- a server arrangement comprising a plurality of processors, wherein the server arrangement is configured to enable communication between the plurality of terminal devices via a communication network, and the plurality of processors are configured to:
- receive, in real time, the communication between the plurality of terminal devices;
- extract the communication to obtain information communicated between the plurality of terminal devices;
- identify the selective information from the communicated information;
- dynamically update the identified selective information until the communication between the plurality of terminal devices terminates; and
- transmit the updated selective information to at least one terminal device of the plurality of the terminal devices.
Embodiments of the disclosure are advantageous in terms of providing an easy-to-use system for live-integrative online shopping. Specifically, the system for live-integrative online shopping enhances the buyers experience and eases the process item selection in online shopping. Moreover, the system for live-integrative online shopping provides an opportunity to the buyer and seller interact during the shopping session and to negotiate over the terms acquisition of an item.
Optionally, the user interface is configured to receive at least one user input.
Optionally, the at least one user input is communicated between the plurality of terminal devices.
Optionally, the processor employs at least one artificial intelligence algorithm to identify the selective information and dynamically update the identified selective information.
Optionally, when executed application enables the at least one buyer computing device to view all possible pricing models based on the sleeted mode of delivery.
Optionally, the at least one artificial intelligence algorithm is trained in at least one of a supervised manner or an unsupervised manner to identify the selective information and dynamically update the identified selective information.
In another aspect, an embodiment of the present disclosure provides a method for identifying selective information, the method comprising:
- receiving, in real time, the communication between the plurality of terminal devices;
- extracting the communication to obtain information communicated between the plurality of terminal devices;
- identifying a selective information from the communicated information;
- dynamically updating the identified selective information until the communication between the plurality of terminal devices terminates; and
- transmitting the updated selective information to at least one terminal device of the plurality of the terminal devices.
Optionally, the method comprises receiving at least one user input.
Optionally, the method comprises communicating the at least one user input between the plurality of terminal devices.
Optionally, the method comprises employing at least one artificial intelligence algorithm to identify the selective information and dynamically update the identified selective information.
Optionally, the method comprises training the at least one artificial intelligence algorithm in at least one of a supervised manner or an unsupervised manner to identify the selective information and dynamically update the identified selective information.
Additional aspects, advantages, features and objects of the present disclosure would be made apparent from the drawings and the detailed description of the illustrative embodiments construed in conjunction with the appended claims that follow.
It will be appreciated that features of the present disclosure are susceptible to being combined in various combinations without departing from the scope of the present disclosure as defined by the appended claims.
BRIEF DESCRIPTION OF THE DRAWINGS
The summary above, as well as the following detailed description of illustrative embodiments, is better understood when read in conjunction with the appended drawings. For the purpose of illustrating the present disclosure, exemplary embodiments of the disclosure are shown in the drawings. However, the present disclosure is not limited to specific methods and instrumentalities disclosed herein. Moreover, those skilled in the art will understand that the drawings are not to scale. Wherever possible, like elements have been indicated by identical numbers.
Embodiments of the present disclosure will now be described, by way of example only, with reference to the following diagrams wherein:
FIG. 1 is a block diagram of a system for identifying selective information, in accordance with an embodiment of the present disclosure; and
FIG. 2 is a flow chart of steps a method for identifying selective information, in accordance with an embodiment of the present disclosure.
In the accompanying drawings, an underlined number is employed to represent an item over which the underlined number is positioned or an item to which the underlined number is adjacent. A non-underlined number relates to an item identified by a line linking the non-underlined number to the item. When a number is non-underlined and accompanied by an associated arrow, the non-underlined number is used to identify a general item to which the arrow is pointing.
DETAILED DESCRIPTION
The following detailed description illustrates embodiments of the present disclosure and ways in which they can be implemented. Although some modes of carrying out the present disclosure have been disclosed, those skilled in the art would recognise that other embodiments for carrying out or practising the present disclosure are also possible.
In one aspect, an embodiment of the present disclosure provides a system for identifying selective information, wherein the system comprises:
- a plurality of terminal devices, wherein the plurality of terminal devices comprises at least one user interface; and
- a server arrangement comprising a plurality of processors, wherein the server arrangement is configured to enable communication between the plurality of terminal devices via a communication network, and the plurality of processors are configured to:
- receive, in real time, the communication between the plurality of terminal devices;
- extract the communication to obtain information communicated between the plurality of terminal devices;
- identify the selective information from the communicated information;
- dynamically update the identified selective information until the communication between the plurality of terminal devices terminates; and
- transmit the updated selective information to at least one terminal device of the plurality of the terminal devices.

In another aspect, an embodiment of the present disclosure provides a method for identifying selective information, the method comprising:
- receiving, in real time, the communication between the plurality of terminal devices;
- extracting the communication to obtain information communicated between the plurality of terminal devices;
- identifying a selective information from the communicated information;
- dynamically updating the identified selective information until the communication between the plurality of terminal devices terminates; and
- transmitting the updated selective information to at least one terminal device of the plurality of the terminal devices.
Throughout the present disclosure, the term “online shopping” as used herein relates to the process of buying goods and services from merchants over the Internet, which allows consumers to directly buy goods or services from a seller over the Internet using a web browser or a mobile app.
Throughout the present disclosure, the term “terminal devices” as used herein relates to a computing device associated with (or used by) a seller or a buyer that is capable of enabling the user to perform specific tasks associated with the aforementioned system/method. Furthermore, a terminal device is intended to be broadly interpreted to include any computing device that may be used for voice and/or data communication over a wireless communication network. Examples of terminal device include, but are not limited to, cellular phones, personal digital assistants (PDAs), handheld devices, wireless modems, laptop computers, personal computers, etc. Moreover, the terminal device may alternatively be referred to as a mobile station, a mobile terminal, a subscriber station, a remote station, a user terminal, a terminal, a subscriber unit, an access terminal, etc. Additionally, the terminal device includes a casing, a memory, a processor, a network interface card, a microphone, a speaker, a keypad, a camera and a display. Moreover, the terminal device is to be construed broadly, so as to encompass a variety of different types of mobile stations, subscriber stations or, more generally, communication devices, including examples such as a combination of a data card inserted in a laptop. Such communication devices are also intended to encompass devices commonly referred to as “access terminals”.
Throughout the present disclosure, the term “user interface (UI)” as used herein relates to a structured set of user interface elements rendered on a display screen. Optionally, the user interface (UI) rendered on the display screen is generated by any collection or set of instructions executable by an associated digital system. Additionally, the user interface (UI) is operable to interact with the user to convey graphical and/or textual information and receive input from the user. Specifically, the user interface (UI) used herein is a graphical user interface (GUI). Furthermore, the user interface (UI) elements refer to visual objects that have a size and position in user interface (UI). A user interface element may be visible, though there may be times when a user interface element is hidden. A user interface control is considered to be a user interface element. Text blocks, labels, text boxes, list boxes, lines, and images windows, dialog boxes, frames, panels, menus, buttons, icons, etc. are examples of user interface elements. In addition to size and position, a user interface element may have other properties, such as a margin, spacing, or the like.
Throughout the present disclosure, the term "server arrangement" as used herein refers to hardware, software, firmware, or a combination of these that provides functionality by way of providing resources, data, services, or programs to other servers, and/or the system. Optionally, the at least one server is implemented as at least one of: a cloud server, a local server. Notably, a given server comprises processing capabilities, such that processing tasks are performed by the given server itself.
Throughout the present disclosure, the term "processor" as used herein, relates to a computational element that is operable to respond to and process instructions. Optionally, the processor includes, but is not limited to, a microprocessor, a microcontroller, a complex instruction set computing (CISC) microprocessor, a reduced instruction set (RISC) microprocessor, a very long instruction word (VLIW) microprocessor, or any other type of processing circuit. Further, the term processor may refer to an individual processor, processing device and various elements associated with a processing device that may be shared by other processing devices. Additionally, the individual processor, processing device and elements are arranged in various architectures for responding to and processing the instructions.
In an example, the server arrangement is coupled to the terminal devices using a communication network. Examples of the communication network include, but are not limited to, a cellular network, short range radio (for example, such as Bluetooth®), Internet, a wired or wireless local area network, and an Infrared Local Area Network, or any combination thereof.
Throughout the present disclosure, the phrase “receive, in real time, communication” as used herein relates to communication information, received by the server arrangement, wherein the communication occurs between the multiple terminal devices. Moreover, the server arrangement enables a mode of communication between the multiple terminal devices. It would be appreciated that the server arrangement that receives the communication information in real-time, via a plurality of processors, enables the system to function in real-time and stay updated.
Throughout the present disclosure, the phrase “extract the communication” as used herein relates to the communication information, extracted by the server arrangement, wherein the communication occurs between the multiple terminal devices.
Throughout the present disclosure, the phrase “obtain information” as used herein relates to conversational information, obtained by the server arrangement, wherein the conversational information corresponds to conversation occurred between multiple users, via the multiple terminal devices. Optionally, a mode of conversation between multiple users may include but not limited to voice call, video call, email, text message and so on. It would be appreciated that the server arrangement that extracts the communication information, via the plurality of processors, leads to fast processing since the plurality of processors require the communication information to obtain the conversational information.
Throughout the present disclosure, the phrase “selective information” as used herein relates to specific conversational information that is a specific portion of entire conversational information. Additionally, the phrase “identify the selective information” as used herein relates to identification of the specific conversational information by the server arrangement, based on a match of the specific conversational information with specific keywords that are pre-stored in a database. It would be appreciated that the server arrangement that identifies the specific conversational information, via the plurality of processors, makes the system and method for identification of selective information more efficient and user friendly, if compared to conventional systems and/or methods.
Throughout the present disclosure, the phrase “dynamically update the identified selective information” as used herein relates to the identified specific conversational information that is dynamically updated by the server arrangement until the communication between the multiple terminal devices terminates. Moreover, the server arrangement dynamically updates the identified specific conversational information in the database until the communication between the multiple terminal devices terminates. Optionally, the server arrangement dynamically updates the identified specific conversational information without using the database. It would be appreciated that the server arrangement that dynamically updates the identified specific conversational information, via the plurality of processors, leads to fast processing, and makes the system and method for identification of selective information more efficient, if compared to conventional systems and/or methods.
Throughout the present disclosure, the phrase “transmit the updated selective information” as used herein relates to transmission of lastly updated specific conversational information. More specifically, the lastly updated specific conversational information, corresponding a subsequent specific portion of the entire conversational information, is updated at last, prior to the termination of communication between the multiple terminal devices.
Throughout the present disclosure, the phrase “user input” as used herein relates to information or data fed to the terminal device, by a user, for processing. Optionally, different types of user input may include but not limited to voice command, textual command, touch command via the user interface and so on.
Throughout the present disclosure, the term “seller” as used herein relates to the user or an individual or an entity that offers a good, service, or asset in return for payment.
Throughout the present disclosure, the term “buyer” or “buyers” as used herein relates to the user or a person or group of persons who is willing to acquire an item of interest/choice or service in exchange of a payment in a physical or online shopping environment or space.
Throughout the present disclosure, the term “artificial intelligence algorithm” as used herein relates to any collection or set of instructions executable by a computer or other digital system so as to configure the computer or the digital system to perform a task that is the intent of the process. Additionally, the process is intended to encompass such instructions stored in storage medium such as RAM, a hard disk, optical disk, or so forth, and is also intended to encompass so-called “firmware” that is software stored on a ROM or so forth. Optionally, the process refers to software application. Such process is organized in various ways, for example the process includes software components organized as libraries, Internet-based programs stored on a remote server or so forth, source code, interpretive code, object code, directly executable code, and so forth. It may be appreciated that the software may invoke system-level code or calls to other software residing on a server or other location to perform certain functions. Furthermore, the process may be pre-configured and pre-integrated with an operating system, building a software appliance. The terms application, process and software may be interchangeable. Further, the term “artificial intelligence algorithm” as used herein relates to a set of functions that can be called from an application program to access features of another program. Furthermore, the application programming interface (API) is a software interface that includes one or more routines, data structures, object classes, and/or protocols that support the interaction of an archiving platform and a storage system. An application programming interface (API), for example, includes building blocks for enabling the building of a software application that is consistent with a particular application or operating environment. An API can be specified in terms of a programming language that can be compiled at application build time.
Throughout the present disclosure, the phrase “training the at least one artificial intelligence algorithm” as used herein relates to the artificial intelligence algorithm that is trained with labelled data of conversation, occurred between the multiple users, captured previously from the conversation occurred at different instances. The conversation between the multiple users occurs via the multiple terminal devices.
Throughout the present disclosure, the term “database” as used herein relates to an organized body of digital information regardless of the manner in which the data or the organized body thereof is represented. Optionally, the database may be hardware, software, firmware and/or any combination thereof. For example, the organized body of related data may be in the form of a table, a map, a grid, a packet, a datagram, a file, a document, a list or in any other form. The database includes any data storage software and systems, such as, for example, a relational database like IBM DB2 and Oracle 9. Optionally, the database may be used interchangeably herein as database management system, as is common in the art. Furthermore, the database management system refers to the software program for creating and managing one or more databases. Optionally, the database may be operable to support relational operations, regardless of whether it enforces strict adherence to the relational model, as understood by those of ordinary skill in the art. Additionally, the database populated by data elements. Furthermore, the data elements may include data records, bits of data, cells, are used interchangeably herein and all intended to mean information stored in cells of a database.
Throughout the present disclosure, the term “Artificial intelligence (AI)” as used herein relates to any mechanism or computationally intelligent system that combines knowledge, techniques, and methodologies for controlling a bot or other element within a computing environment. Furthermore, the artificial intelligence (AI) is configured to apply knowledge and that can adapt it-self and learn to do better in changing environments. Additionally, employing any computationally intelligent technique, the artificial intelligence (AI) is operable to adapt to unknown or changing environment for better performance. The artificial intelligence (AI) includes fuzzy logic engines, decision-making engines, pre-set targeting accuracy levels, and/or programmatically intelligent software.
Artificial intelligence (AI) in the context of the present disclosure relates to software-based algorithms that are executable upon computing hardware and are operable to adapt and adjust their operating parameters in an adaptive manner depending upon information that is presented to the software-based algorithms when executed upon the computing hardware. Optionally, the artificial intelligence (AI) includes neural networks such as recurrent neural networks, recursive neural networks, feed-forward neural networks, convolutional neural networks, deep belief networks, and convolutional deep belief networks; self-organizing maps; deep Boltzmann machines; and stacked de-noising auto-encoders. An “artificial neural network” or simply a “neural network” as used herein can include a highly interconnected network of processing elements, each optionally associated with a local memory. In an example, the neural network may be Kohonen map, multi-layer perceptron and so forth. The processing elements can be referred to herein as “artificial neural units,” “artificial neurons,” “neural units,” “neurons,” “nodes,” and the like, while connections between the processing elements. A neuron can receive data from an input or one or more other neurons, process the data, and send processed data to an output or yet one or more other neurons. The neural network or one or more neurons thereof can be generated in either hardware, software, or a combination of hardware and software, and the neural network can be subsequently trained.
Optionally, artificial intelligence (AI) employs any one or combination of the following computational techniques: constraint program, fuzzy logic, classification, conventional artificial intelligence, symbolic manipulation, fuzzy set theory, evolutionary computation, cybernetics, data mining, approximate reasoning, derivative-free optimization, decision trees, or soft computing.
Now referring to Fig. 1, there is disclosed a system 100 for identifying selective information, in accordance with an embodiment of the present disclosure. The system 100 comprises a plurality of terminal devices 102 and 104, and a server arrangement 106. Further, the plurality of terminal devices 102 and 104 includes at least one user interface, and the server arrangement 106 includes the plurality of processors. Specifically, when the server arrangement 106 enables communication between the plurality of terminal devices 102 and 104 via a communication network, the plurality of processors of the server arrangement 106 receives, in real time, the communication between the plurality of terminal devices 102 and 104, extracts the communication to obtain information communicated between the plurality of terminal devices 102 and 104, identifies the selective information from the communicated information, dynamically updates the identified selective information until the communication between the plurality of terminal devices 102 and 104 terminates, and transmits the updated selective information to at least one terminal device of the plurality of the terminal devices 102 and 104
Embodiments of the disclosure are advantageous in terms of providing an easy-to-use system for live-integrative online shopping. Specifically, the system for live-integrative online shopping enhances the buyers experience and eases the process item selection in online shopping. Moreover, the system for live-integrative online shopping provides an opportunity to the buyer and seller interact during the shopping session and to negotiate over the terms acquisition of an item.
Additionally, the system for live-integrative online shopping provides a loyalty or reward program that allows any seller, regardless of its size, to award their own branded rewards such as reward points and allow buyers to redeem them for their own products or services in order to build brand loyalty for that seller. It is also desired to allow buyers to selectively redeem their reward points with other sellers that are part of the network. The reward points or loyalty coins are awarded by the seller to buyers based on certain parameters. More specifically, based on a number of items bought, a first-time buyer, a value of bill or invoice, etc.
Moreover, embodiments of the disclosure are advantageous to a seller or a retailer in terms of eliminating the requirement of large display space and fancy showrooms. Thus, significantly increasing financial margins associated with the item for sale and consequently making the item available to the buyers on relatively low cost.
In an embodiment, the buyer who operates the terminal device 102 may connect, via the server arrangement 106, to an available seller who operates the terminal device 104, for acquiring at least one item of choice based on at least one of geographical location, delivery time, bulk availability, discounts, group discounts and so forth with reference to the location of the buyer who operates the terminal device 102 or the delivery location.
In an exemplary embodiment, the reference location of the buyer’s terminal device 102 may be based on Global Positioning System (GPS) location of the terminal device 102. Alternatively, Postal Index Number (PIN Code) may be used to identify location of the buyer’s terminal device 102 and/or the delivery location.
In an embodiment, the available seller’s terminal device 104 may be categorized in sub-categories such as near-by sellers, out-of-station sellers, same-day delivery, next-day delivery and so forth.
In an embodiment, the application may rank the sellers in a specific order. Specifically, the application may implement Machine Learning (ML) and/or Artificial Intelligence for ranking the buyers in real-time manner. Specifically, parameters for ranking the buyers may include but not limited to third party rating(s), buyers rating(s), number of agents, number of orders processed, number of calls answered, number of orders created, number of favourites, number of agreed reports, number of calls missed and so forth.
Optionally, ranking of the buyers by implementing Machine Learning (ML) and/or Artificial Intelligence includes variable such as the above-mentioned parameters, value parameters (VP1, VP2…...VPn), Current universal highest of the parameter on the application (HP1, HP2…..), Current universal lowest of the parameter on the applications (LP1, LP2….), Total Value (TV), Seller data for all the above-mentioned parameters (CP1, CP2……) and total for the seller with rank one. Specifically, the value parameters (VP1, VP2…...VPn) are dynamic in nature.
Moreover, calculation of ranks for the sellers in real-time manner includes calculation of parameter total according to the real-time current data of the seller and/or seller computing devise(s), calculating equivalent parameter total and adding all equivalent parameter totals for obtaining ranking for the seller.
Specifically, calculation of parameter total according to the real-time current data of the seller and/or seller’s terminal devise(s) 104 includes listing of down current data for all parameters (CPn) and calculating the different parameter totals, wherein for seller;

PT1 = [(CP1)/(HP1 – LP1)]
Further, the equivalent parameter total, for seller one, is calculated using the below mentioned formula;
Equivalent parameter total (EP1T1) = (VP1 * PT1)
Furthermore, equivalent parameter total and adding all equivalent parameter totals for seller 1 is calculated using the below mentioned formula;
S1R = SUM (EP1T1 + EP2T2 + EP3T3 + EP4T4 + …… EPNTN)
wherein S1R is the ranking total of the seller one.
Additionally, the parameters for ranking the sellers may further sub categorized to positive parameters and negative parameters. Specifically, the positive parameters contribute positive to the sum and the negative parameters contributes negative to the sum.
In an embodiment, a seller may include multiple terminal devices allocated to individual salespersons. Further, the salespersons within a shop may be ranked accordingly based on the abovementioned parameters in real-time manner.
In another embodiment, a buyer may create a virtual shopping mall by adding a plurality of sellers for variety of items of choice to the favourite list.
In yet another embodiment, the buyer may narrow down his/her search of relevant item of choice by restricting the listed items of choice with at least one item property. Additionally, the server arrangement 106 allows the selected item property(ies) to be displayed on the seller’s terminal device and the buyer’s terminal device.
Optionally, the server arrangement 106 may cause the at least one buyer’s terminal device 102 to select at least one of an instant payment option or a delayed payment option for acquiring at least one item of choice. Specifically, in the instant payment option the payment link is shared with the buyer’s terminal device 102 in real time manner. Additionally, the payment link includes a sum of cost of the item to be acquired and the delivery charges based on selected mode delivery.
In an embodiment, the server arrangement 106 enables the buyer to view the over all cost for acquiring at least one item of choice including the negotiated cost of the item and cost for different modes of delivery.
Alternatively, the delayed payment option enables the buyer to fix a cost for acquiring at least one item of choice and discuss the same with his/her friends and/or family and quire the item of choice.
In yet another embodiment, the delivery mode may include but not limited to a seller delivery, a third-party delivery or a buyer collection.
Now referring to Fig. 2, there is disclosed a method 200 for identifying selective information, in accordance with an embodiment of the present disclosure. The method initiates at a step 202, At the step 202, the method 200 includes receiving, via the server arrangement 106, in real time, the communication between the plurality of terminal devices 102 and 104. At a step 204, the method 200 includes extracting, via the server arrangement 106, the communication to obtain information communicated between the plurality of terminal devices102 and 104. At a step 206, the method 200 includes identifying, via the server arrangement 106, a selective information from the communicated information. At a step 208, the method 200 includes dynamically updating, via the server arrangement 106, the identified selective information until the communication between the plurality of terminal devices 102 and 104 terminates. At a step 210, the method 200 includes transmitting, via the server arrangement 106, the updated selective information to at least one terminal device of the plurality of the terminal devices102 and 104. The method 200 ends at the step 210.
The present disclosure also relates to the method as described above. Various embodiments and variants disclosed above apply mutatis mutandis to the method.
Optionally, the method comprises selecting, via the at least one buyer’s terminal device 102, at least one of an instant payment option or a delayed payment option for acquiring at least one item of choice.
Optionally, the method comprises ranking the at least one available buyer’s terminal device 102 based on a plurality of pre-defined parameters.
Optionally, the method comprises viewing, via the at least one terminal device 102 or 104, all possible pricing models based on the sleeted mode of delivery.
Optionally, the mode of delivery includes one of a seller delivery, a third party delivery or a buyer collection.
Modifications to embodiments of the present disclosure described in the foregoing are possible without departing from the scope of the present disclosure as defined by the accompanying claims. Expressions such as “including”, “comprising”, “incorporating”, “have”, “is” used to describe and claim the present disclosure are intended to be construed in a non-exclusive manner, namely allowing for items, components or elements not explicitly described also to be present. Reference to the singular is also to be construed to relate to the plural where appropriate.
Additional aspects, advantages, features and objects of the present disclosure would be made apparent from the drawings and the detailed description of the illustrative embodiments construed in conjunction with the appended claims that follow.
It will be appreciated that features of the present disclosure are susceptible to being combined in various combinations without departing from the scope of the present disclosure as defined by the appended claims.
, Claims:We Claim:
1. A system for identifying selective information, wherein the system comprises:
- a plurality of terminal devices, wherein the plurality of terminal devices comprises at least one user interface; and
- a server arrangement comprising a plurality of processors, wherein the server arrangement is configured to enable communication between the plurality of terminal devices via a communication network, and
the plurality of processors are configured to:
- receive, in real-time, the communication between the plurality of terminal devices;
- extract the communication to obtain information communicated between the plurality of terminal devices;
- identify the selective information from the communicated information;
- dynamically update the identified selective information until the communication between the plurality of terminal devices terminates; and
- transmit the updated selective information to at least one terminal device of the plurality of the terminal devices.
2. The system as claimed in claim 1, wherein the user interface is configured to receive at least one user input.
3. The system as claimed in claim 2, wherein the at least one user input is communicated between the plurality of terminal devices.
4. The system as claimed in claim 1, wherein the processor employs at least one artificial intelligence algorithm to identify the selective information and dynamically update the identified selective information.
5. The system as claimed in claim 4, wherein the at least one artificial intelligence algorithm is trained in at least one of a supervised manner or an unsupervised manner to identify the selective information and dynamically update the identified selective information.
6. A method for identifying selective information, the method comprising:
- receiving, in real time, the communication between the plurality of terminal devices;
- extracting the communication to obtain information communicated between the plurality of terminal devices;
- identifying a selective information from the communicated information;
- dynamically updating the identified selective information until the communication between the plurality of terminal devices terminates; and
- transmitting the updated selective information to at least one terminal device of the plurality of the terminal devices.
7. The method as claimed in claim 6, wherein the method further comprises receiving at least one user input.
8. The method as claimed in claim 7, wherein the method further comprises communicating the at least one user input between the plurality of terminal devices.
9. The method as claimed in claim 6, wherein the method further comprises employing at least one artificial intelligence algorithm to identify the selective information and dynamically update the identified selective information.
10. The method as claimed in claim 9, wherein the method further comprises training the at least one artificial intelligence algorithm in at least one of a supervised manner or an unsupervised manner to identify the selective information and dynamically update the identified selective information.