WO2015080563A1 - A system and method for instant messaging platform - Google Patents

A system and method for instant messaging platform Download PDF

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Publication number
WO2015080563A1
WO2015080563A1 PCT/MY2014/000177 MY2014000177W WO2015080563A1 WO 2015080563 A1 WO2015080563 A1 WO 2015080563A1 MY 2014000177 W MY2014000177 W MY 2014000177W WO 2015080563 A1 WO2015080563 A1 WO 2015080563A1
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WIPO (PCT)
Prior art keywords
instant messaging
user
generator
rich content
semantic
Prior art date
Application number
PCT/MY2014/000177
Other languages
French (fr)
Inventor
Yusrin Bin Amruddin AMRU
Yew Choong CHEW
Helmy Bin Abdul Shukor MUHAMMAD
A/L M. Perumal NAGENDRAN
Original Assignee
Mimos Berhad
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Publication of WO2015080563A1 publication Critical patent/WO2015080563A1/en

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    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06QINFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
    • G06Q50/01Social networking
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06NCOMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N5/00Computing arrangements using knowledge-based models
    • G06N5/02Knowledge representation; Symbolic representation
    • G06N5/022Knowledge engineering; Knowledge acquisition
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06QINFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q30/00Commerce
    • G06Q30/06Buying, selling or leasing transactions
    • G06Q30/0601Electronic shopping [e-shopping]
    • G06Q30/0631Item recommendations

Definitions

  • the present invention relates to a system and method for providing an instant messaging platform. More particularly, the present invention relates to a system and method for providing an instant messaging platform capable of identifying contacts based on similar interest and providing additional information based on user's text messages.
  • instant messaging platform has become an imperative means of communication.
  • instant messaging platform allows a user to define a list of contacts and to reject and ignore messages sent by other users.
  • a few improvements have been made to the instant messaging platform to provide a better service for the user.
  • the user needs to have the other user ID and obtains approval from the other user to add them in the user contact list wherein the user usually identifies the contacts.
  • a several methods are disclosed in the prior arts in adding and identifying the other user. An example of such method and system is disclosed in US Publication No.
  • 2011/0289011 A1 wherein the method and system is directed towards seeding a user's contacts for their online social network.
  • the system is arranged to automatically recommend to the user a set of seed contacts that the user may employ to invite to join their social network.
  • the set of seed contacts may be harvested from the user's existing portal activities, as well as other sources.
  • the invention analyses portal activity, such as email exchanges with the user, and the like, to determine a frequency of contact with the user.
  • this method and system is provided for online social networking wherein the prior art identifies contacts based on frequency of interaction through other means such as chats and emails.
  • US Publication No. 2008/0288467 A1 discloses a technique for integrating instant messaging with Internet search features.
  • An instant messaging (IM) application allows users to launch a search of the Internet or the World Wide Web for information about another IM user or another topic. If an IM user wishes to locate information relating to a friend, a search is performed through a database of registered IM members to locate a user profile for the friend. If the friend's profile is found, the profile is displayed to the IM user. The searching is manually done by the user wherein the user has to manually launch the Internet search for information relating to the topic or friend.
  • IM instant messaging
  • a system (100) for instant messaging comprises of an instant messaging client, wherein the instant messaging client is a client component installed in a user device; wherein the system (100) is characterised in that it further includes an instant messaging intelligence platform for providing a list of contacts having similar interest with a user and suggesting rich content related to text messages inputted by the user, wherein the instant messaging intelligence platform is connected to the instant messaging client; and a knowledge based ontology (150) and Internet (160) connected to the instant messaging intelligence platform.
  • the instant messaging intelligence platform comprises of a Chat Entry Box (110) to display the input data from user, wherein the Chat Entry Box (110) displays text messages between users; a Semantic Keyword Generator (120) to extract keywords from the text messages in the Chat Entry Box (110); a Rich Content Generator (130) to display a suggested content related to the text messages in the Chat Entry Box (110), wherein the suggested content is generated by using the knowledge based ontology (150); and a Semantic Match Maker (140) to provide a list of potential contacts having similar interest with a user of the instant messaging intelligence platform, wherein the list of potential contact is suggested based on the keywords extracted by the Semantic Keyword Generator (120).
  • a Semantic Keyword Generator 120
  • Rich Content Generator 130
  • Semantic Match Maker 140
  • the Rich Content Generator (130) includes a Term Frequency Calculator to determine the frequency of occurrence of the keywords used in the text messages in the Chat Entry Box (110).
  • a method for instant messaging is characterised by the steps of receiving input data in the Chat Entry Box (110) from a user; extracting keywords based on the input data in the Chat Entry Box (110) by the Semantic Keyword Generator (120); forwarding extracted keywords to the Rich Content Generator (130) and the Semantic Match Maker (140) by the Semantic Keyword Generator (120); suggesting relevant rich content to the user by the Rich Content Generator (130) based on the extracted keyword; and matching similar interest contacts by the Semantic Match Maker (140) based on the keywords extracted by the Semantic Keyword Generator (120).
  • extracting keywords based on input data from the user by the Semantic Keyword Generator (120) includes the steps of analysing textual entry in the Chat Entry Box (110); assigning the textual entry to the text entry area; dividing the textual entry to an array of texts; identifying noun in the array of texts; tagging the identified noun from the array of texts as keyword, validating the combination of nouns if there is adjacent noun; and tagging and forwarding the combination of nouns as keyword to the Rich Content Generator (130) and the Semantic Match Maker (140) if the combination of nouns is valid.
  • Semantic Keyword Generator includes the step of returning empty string as the keyword if there is no adjacent noun identified or if the combination of nouns is invalid. Preferably, suggesting the relevant rich content by the Rich Content
  • the Rich Content Generator (130) includes the steps of receiving the extracted keyword by the rich Content Generator (130); sending the extracted keyword to the knowledge based ontology (160); categorising the results from the search into links, videos, images and keywords; determining and assigning order of relevance of the frequency of occurrence of the extracted keywords in each result by the Term Frequency Calculator of the Rich Content Generator (130); and displaying the list of the relevant rich content ranked by relevance by the Rich Content Generator (130).
  • matching similar interest contacts by the Semantic Match Maker (140) includes the steps of receiving the extracted keywords by the Semantic Match Maker (140); storing the extracted keywords as a topic of interest in the user profile; updating the topic of interest in the user profile if new topic of interest is been introduced; comparing the user profile with the profile of other users and chat rooms by the Semantic Match Maker (130); and displaying the profile of the listed contacts and chat rooms by the Semantic Match Maker (140).
  • FIG. 1 illustrates a block diagram of a system (100) for instant messaging according to an embodiment of the present invention.
  • FIG. 2 illustrates a flowchart of a method for instant messaging of the system (100) according to an embodiment of the present invention.
  • FIG. 3 illustrates a flowchart of sub-steps for extracting keywords based on input data from users of the method of FIG. 2.
  • FIG. 4 illustrates a flowchart of sub-steps for suggesting relevant rich content by a Rich Content Generator (130) of the method of FIG. 2.
  • FIG. 5 illustrates a flowchart of sub-steps for matching up similar interest contact by a Semantic Match Maker (140) of the method of FIG. 2.
  • FIG. 1 shows a block diagram of a system (100) for instant messaging according to an embodiment of the present invention.
  • the system (100) comprises of an instant messaging client and an instant messaging intelligence platform.
  • the instant messaging client is a client component installed in a user device such as mobile device, computer, laptop and tablet, whereas the instant messaging intelligence platform is used for providing a list of contacts having similar interest with a user and suggesting rich content related to text messages inputted by the user.
  • the instant messaging client is connected to the instant messaging intelligence platform.
  • the instant messaging intelligence platform is also connected to a knowledge based ontology (150) and Internet (160).
  • the instant messaging intelligence platform comprises of a Chat Entry Box (110), a Semantic Keyword Generator (120), a Rich Content Generator (130) and a Semantic Match Maker (140).
  • the Chat Entry Box (110) is used to display the input data from users, wherein the Chat Entry Box (110) displays the text messages between users.
  • the Semantic Keyword Generator (120) is used to extract keywords from the text messages between users.
  • the Rich Content Generator (130) is used to display a relevant rich content related to text messages inputted by the user.
  • the relevant rich content is generated by the Rich Content Generator (130) by using the knowledge based ontology (150) such as Wordnet and the Internet (160) such as blog and Wikipedia to search for related links, images and videos.
  • the related links, images and videos are suggested based on the frequently used keywords.
  • the Rich Content Generator (130) includes a Term Frequency Calculator to determine the frequency of occurrence of the keywords used in the text messages in the Chat Entry Box (110).
  • the Semantic Match Maker (140) provides a list of potential contacts having similar interest with the user of the system (100). The list of potential contacts is suggested based on the keywords extracted by the Semantic Keyword Generator (120).
  • FIG. 2 shows a flowchart of a method for instant messaging of the system
  • the user inputs data such as text messages, images or videos into the Chat Entry Box (110) via the instant messaging client as in step 210.
  • the Semantic Keyword Generator (120) extracts keywords to be displayed for the user to select as in step 220.
  • the keywords are extracted based on the frequent keywords used by the user in the text messages of the input data in the Chat Entry Box (110).
  • the Semantic Keyword Generator (120) forwards the extracted keywords to the Rich Content Generator (130) as in step 230 to provide suggestion of relevant rich content, wherein the rich content is a combination of several types of media such as text, images and videos.
  • the Rich Content Generator (130) suggests the relevant rich content wherein the Rich Content Generator (130) displays the list of the relevant rich content ranked by relevance to the user.
  • the user selects the desired content via the instant messaging client and shares the rich content with other contacts.
  • the Semantic Keyword Generator (120) forwards the frequent keywords used in the text messages to the Semantic Match Maker (140) as in step 240.
  • the Semantic Match Maker (140) stores the extracted keywords by identifying them as areas of interest for a particular user to be compared with other contacts' interests. Then, the user is matched with contacts having similar interests wherein the user is given a selection of contacts having similar interest to select so as to communicate through instant messaging.
  • FIG. 3 shows a flowchart of sub-steps for extracting keywords based on input data from the user of the system (100) as in step 220 of the method of FIG. 2.
  • the Semantic Keyword Generator (120) analyses the textual entry made by the users in the Chat Entry Box (110) and extracts the keywords from the entry.
  • the Semantic Keyword Generator (120) assigns the textual entry to the text entry area.
  • the entry is divided into an array of texts as in step 222. Nouns in the array of texts are identified as in decision 223 by comparing the nouns with the knowledge based ontology (150) such as Word Net and websites on the Internet (160) such as Wikipedia, Google, Bing, Yahoo and Yebol.
  • the Semantic Keyword Generator (120) returns empty string as the keyword. If there is a noun identified from the array of texts, the noun is tagged as a keyword and thereon, any adjacent noun is identified noun as in decision 224. If there is no adjacent noun, the identified noun is tagged as a keyword and forwarded to the Rich Content Generator (130) and the Semantic Match Maker (140) as in step 226. If there is an adjacent noun, the combination of the noun and the adjacent noun is validated via Word Net and Wikipedia as in decision 225.
  • FIG. 4 shows a flowchart of sub-steps for suggesting relevant rich content by the Rich Content Generator (130) as in step 230 of the method of FIG. 2.
  • the Rich Content Generator (130) receives the extracted keyword as in step 231 and sends them to the knowledge based ontology (150) as in step 232.
  • the knowledge based ontology (150) searches for rich content related to the keywords. Thereon, the results from the search are categorised into links, videos, images and keywords as in step
  • the Term Frequency Calculator determines the frequency of occurrence of the related keywords in each result and assigns the order of relevance to it as in step
  • the Rich Content Generator displays the results in the order of relevance based on the output produced by the Term Frequency Calculator as in step 235.
  • FIG. 5 shows a flowchart of a method for matching similar interest contacts by the Semantic Match Maker (140) as in step 240 of the method of FIG. 2.
  • the Semantic Match Maker (140) receives the extracted keywords from the Semantic Keyword Generator (120).
  • the extracted keywords are then automatically stored as a topic of interest in the user profile as in step 242 and the topic of interest in the user profile is updated if new topic of interest is introduced by the user in the Chat Entry Box (110).
  • the user of the system (100) has their own profile stored in a database wherein the user profile includes a basic biographical data of the user such as name, email and address.
  • the instant messaging intelligence platform monitors conversations in chat rooms and creates a profile for each chat room wherein the chat room comprises of a list of suggested contacts based on profile matching.
  • the Semantic Match Maker (130) compares the user profile with the profile of other existing users and chat rooms.
  • the Semantic Match Maker (140) displays the profile of the listed contacts and chat rooms before starting a conversation with the selected contact wherein the profile is real time automatically setup by the system (100) based on the text messages. While embodiments of the invention have been illustrated and described, it is not intended that these embodiments illustrate and describe all possible forms of the invention. Rather, the words used in the specifications are words of description rather than limitation and various changes may be made without departing from the scope of the invention.

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Abstract

The present invention relates to a system and method for providing an instant messaging service that incorporates the capability to intelligently identify contacts having similar interest. The system (100) comprises of an instant messaging client and an instant messaging intelligence platform wherein the instant messaging intelligence platform comprises of a Chat Entry Box (110), a Semantic Keyword Generator (120), a Rich Content Generator (130) and a Semantic Match Maker (140). The instant messaging intelligence platform is also connected to a knowledge based ontology (150) and Internet (160).

Description

A SYSTEM AND METHOD FOR INSTANT MESSAGING PLATFORM
FIELD OF INVENTION
The present invention relates to a system and method for providing an instant messaging platform. More particularly, the present invention relates to a system and method for providing an instant messaging platform capable of identifying contacts based on similar interest and providing additional information based on user's text messages. BACKGROUND OF THE INVENTION
Nowadays, instant messaging platform has become an imperative means of communication. Currently, instant messaging platform allows a user to define a list of contacts and to reject and ignore messages sent by other users. A few improvements have been made to the instant messaging platform to provide a better service for the user. Typically, the user needs to have the other user ID and obtains approval from the other user to add them in the user contact list wherein the user usually identifies the contacts. A several methods are disclosed in the prior arts in adding and identifying the other user. An example of such method and system is disclosed in US Publication No.
2011/0289011 A1 wherein the method and system is directed towards seeding a user's contacts for their online social network. The system is arranged to automatically recommend to the user a set of seed contacts that the user may employ to invite to join their social network. The set of seed contacts may be harvested from the user's existing portal activities, as well as other sources. In one embodiment, the invention analyses portal activity, such as email exchanges with the user, and the like, to determine a frequency of contact with the user. However this method and system is provided for online social networking wherein the prior art identifies contacts based on frequency of interaction through other means such as chats and emails.
On the other hand, US Publication No. 2008/0288467 A1 discloses a technique for integrating instant messaging with Internet search features. An instant messaging (IM) application allows users to launch a search of the Internet or the World Wide Web for information about another IM user or another topic. If an IM user wishes to locate information relating to a friend, a search is performed through a database of registered IM members to locate a user profile for the friend. If the friend's profile is found, the profile is displayed to the IM user. The searching is manually done by the user wherein the user has to manually launch the Internet search for information relating to the topic or friend.
Hence, there is a need to improve the existing instant messaging platform by having the capability of automatically providing a list of contacts based on similar interest and suggesting content related to the text messages in the form of links, images and videos.
SUMMARY OF INVENTION
A system (100) for instant messaging comprises of an instant messaging client, wherein the instant messaging client is a client component installed in a user device; wherein the system (100) is characterised in that it further includes an instant messaging intelligence platform for providing a list of contacts having similar interest with a user and suggesting rich content related to text messages inputted by the user, wherein the instant messaging intelligence platform is connected to the instant messaging client; and a knowledge based ontology (150) and Internet (160) connected to the instant messaging intelligence platform.
Preferably, the instant messaging intelligence platform comprises of a Chat Entry Box (110) to display the input data from user, wherein the Chat Entry Box (110) displays text messages between users; a Semantic Keyword Generator (120) to extract keywords from the text messages in the Chat Entry Box (110); a Rich Content Generator (130) to display a suggested content related to the text messages in the Chat Entry Box (110), wherein the suggested content is generated by using the knowledge based ontology (150); and a Semantic Match Maker (140) to provide a list of potential contacts having similar interest with a user of the instant messaging intelligence platform, wherein the list of potential contact is suggested based on the keywords extracted by the Semantic Keyword Generator (120).
Preferably, the Rich Content Generator (130) includes a Term Frequency Calculator to determine the frequency of occurrence of the keywords used in the text messages in the Chat Entry Box (110). A method for instant messaging is characterised by the steps of receiving input data in the Chat Entry Box (110) from a user; extracting keywords based on the input data in the Chat Entry Box (110) by the Semantic Keyword Generator (120); forwarding extracted keywords to the Rich Content Generator (130) and the Semantic Match Maker (140) by the Semantic Keyword Generator (120); suggesting relevant rich content to the user by the Rich Content Generator (130) based on the extracted keyword; and matching similar interest contacts by the Semantic Match Maker (140) based on the keywords extracted by the Semantic Keyword Generator (120).
Preferably, extracting keywords based on input data from the user by the Semantic Keyword Generator (120) includes the steps of analysing textual entry in the Chat Entry Box (110); assigning the textual entry to the text entry area; dividing the textual entry to an array of texts; identifying noun in the array of texts; tagging the identified noun from the array of texts as keyword, validating the combination of nouns if there is adjacent noun; and tagging and forwarding the combination of nouns as keyword to the Rich Content Generator (130) and the Semantic Match Maker (140) if the combination of nouns is valid. Preferably, extracting keywords based on input data from the user by the
Semantic Keyword Generator (120) includes the step of returning empty string as the keyword if there is no adjacent noun identified or if the combination of nouns is invalid. Preferably, suggesting the relevant rich content by the Rich Content
Generator (130) includes the steps of receiving the extracted keyword by the rich Content Generator (130); sending the extracted keyword to the knowledge based ontology (160); categorising the results from the search into links, videos, images and keywords; determining and assigning order of relevance of the frequency of occurrence of the extracted keywords in each result by the Term Frequency Calculator of the Rich Content Generator (130); and displaying the list of the relevant rich content ranked by relevance by the Rich Content Generator (130).
Preferably, matching similar interest contacts by the Semantic Match Maker (140) includes the steps of receiving the extracted keywords by the Semantic Match Maker (140); storing the extracted keywords as a topic of interest in the user profile; updating the topic of interest in the user profile if new topic of interest is been introduced; comparing the user profile with the profile of other users and chat rooms by the Semantic Match Maker (130); and displaying the profile of the listed contacts and chat rooms by the Semantic Match Maker (140).
BRIEF DESCRIPTION OF THE DRAWINGS
The accompanying drawings, which are incorporated in and constitute a part of the specification, illustrate embodiments of the invention and, together with the description, serve to explain the principles of the invention.
FIG. 1 illustrates a block diagram of a system (100) for instant messaging according to an embodiment of the present invention. FIG. 2 illustrates a flowchart of a method for instant messaging of the system (100) according to an embodiment of the present invention.
FIG. 3 illustrates a flowchart of sub-steps for extracting keywords based on input data from users of the method of FIG. 2.
FIG. 4 illustrates a flowchart of sub-steps for suggesting relevant rich content by a Rich Content Generator (130) of the method of FIG. 2.
FIG. 5 illustrates a flowchart of sub-steps for matching up similar interest contact by a Semantic Match Maker (140) of the method of FIG. 2.
DESCRIPTION OF THE PREFFERED EMBODIMENT
A preferred embodiment of the present invention will be described herein below with reference to the accompanying drawings. In the following description, well known functions or constructions are not described in detail since they would obscure the description with unnecessary detail. FIG. 1 shows a block diagram of a system (100) for instant messaging according to an embodiment of the present invention. The system (100) comprises of an instant messaging client and an instant messaging intelligence platform. The instant messaging client is a client component installed in a user device such as mobile device, computer, laptop and tablet, whereas the instant messaging intelligence platform is used for providing a list of contacts having similar interest with a user and suggesting rich content related to text messages inputted by the user. The instant messaging client is connected to the instant messaging intelligence platform. The instant messaging intelligence platform is also connected to a knowledge based ontology (150) and Internet (160).
The instant messaging intelligence platform comprises of a Chat Entry Box (110), a Semantic Keyword Generator (120), a Rich Content Generator (130) and a Semantic Match Maker (140). The Chat Entry Box (110) is used to display the input data from users, wherein the Chat Entry Box (110) displays the text messages between users. The Semantic Keyword Generator (120) is used to extract keywords from the text messages between users. The Rich Content Generator (130) is used to display a relevant rich content related to text messages inputted by the user. The relevant rich content is generated by the Rich Content Generator (130) by using the knowledge based ontology (150) such as Wordnet and the Internet (160) such as blog and Wikipedia to search for related links, images and videos. The related links, images and videos are suggested based on the frequently used keywords. The Rich Content Generator (130) includes a Term Frequency Calculator to determine the frequency of occurrence of the keywords used in the text messages in the Chat Entry Box (110). The Semantic Match Maker (140) provides a list of potential contacts having similar interest with the user of the system (100). The list of potential contacts is suggested based on the keywords extracted by the Semantic Keyword Generator (120). FIG. 2 shows a flowchart of a method for instant messaging of the system
(100) according to an embodiment of the present invention. Initially, the user inputs data such as text messages, images or videos into the Chat Entry Box (110) via the instant messaging client as in step 210. Thereon, based on the input data from the user, the Semantic Keyword Generator (120) extracts keywords to be displayed for the user to select as in step 220. Particularly, the keywords are extracted based on the frequent keywords used by the user in the text messages of the input data in the Chat Entry Box (110). Thereon, the Semantic Keyword Generator (120) forwards the extracted keywords to the Rich Content Generator (130) as in step 230 to provide suggestion of relevant rich content, wherein the rich content is a combination of several types of media such as text, images and videos. Thereon, the Rich Content Generator (130) suggests the relevant rich content wherein the Rich Content Generator (130) displays the list of the relevant rich content ranked by relevance to the user. The user selects the desired content via the instant messaging client and shares the rich content with other contacts. Meanwhile, the Semantic Keyword Generator (120) forwards the frequent keywords used in the text messages to the Semantic Match Maker (140) as in step 240. Based on the extracted keywords forwarded by the Semantic Keyword Generator (120), the Semantic Match Maker (140) stores the extracted keywords by identifying them as areas of interest for a particular user to be compared with other contacts' interests. Then, the user is matched with contacts having similar interests wherein the user is given a selection of contacts having similar interest to select so as to communicate through instant messaging.
FIG. 3 shows a flowchart of sub-steps for extracting keywords based on input data from the user of the system (100) as in step 220 of the method of FIG. 2. The Semantic Keyword Generator (120) analyses the textual entry made by the users in the Chat Entry Box (110) and extracts the keywords from the entry. In step 221 , the Semantic Keyword Generator (120) assigns the textual entry to the text entry area. Thereon, the entry is divided into an array of texts as in step 222. Nouns in the array of texts are identified as in decision 223 by comparing the nouns with the knowledge based ontology (150) such as Word Net and websites on the Internet (160) such as Wikipedia, Google, Bing, Yahoo and Yebol. If there is no noun identified from the array of texts, the Semantic Keyword Generator (120) returns empty string as the keyword. If there is a noun identified from the array of texts, the noun is tagged as a keyword and thereon, any adjacent noun is identified noun as in decision 224. If there is no adjacent noun, the identified noun is tagged as a keyword and forwarded to the Rich Content Generator (130) and the Semantic Match Maker (140) as in step 226. If there is an adjacent noun, the combination of the noun and the adjacent noun is validated via Word Net and Wikipedia as in decision 225. If the combination of nouns is valid, the combination of nouns is tagged as a keyword and forwarded to the Rich Content Generator (130) and the Semantic Match Maker (140) as in step 226. If the combination of nouns is invalid, the Semantic Keyword Generator (120) returns empty string as the keyword. FIG. 4 shows a flowchart of sub-steps for suggesting relevant rich content by the Rich Content Generator (130) as in step 230 of the method of FIG. 2. The Rich Content Generator (130) receives the extracted keyword as in step 231 and sends them to the knowledge based ontology (150) as in step 232. The knowledge based ontology (150) searches for rich content related to the keywords. Thereon, the results from the search are categorised into links, videos, images and keywords as in step
233. The Term Frequency Calculator determines the frequency of occurrence of the related keywords in each result and assigns the order of relevance to it as in step
234. For each category, the Rich Content Generator (130) displays the results in the order of relevance based on the output produced by the Term Frequency Calculator as in step 235.
FIG. 5 shows a flowchart of a method for matching similar interest contacts by the Semantic Match Maker (140) as in step 240 of the method of FIG. 2. In step 241 , the Semantic Match Maker (140) receives the extracted keywords from the Semantic Keyword Generator (120). The extracted keywords are then automatically stored as a topic of interest in the user profile as in step 242 and the topic of interest in the user profile is updated if new topic of interest is introduced by the user in the Chat Entry Box (110). The user of the system (100) has their own profile stored in a database wherein the user profile includes a basic biographical data of the user such as name, email and address. The instant messaging intelligence platform monitors conversations in chat rooms and creates a profile for each chat room wherein the chat room comprises of a list of suggested contacts based on profile matching. In step 243, the Semantic Match Maker (130) compares the user profile with the profile of other existing users and chat rooms. In step 244, the Semantic Match Maker (140) displays the profile of the listed contacts and chat rooms before starting a conversation with the selected contact wherein the profile is real time automatically setup by the system (100) based on the text messages. While embodiments of the invention have been illustrated and described, it is not intended that these embodiments illustrate and describe all possible forms of the invention. Rather, the words used in the specifications are words of description rather than limitation and various changes may be made without departing from the scope of the invention.

Claims

A system (100) for instant messaging comprises of:
a) an instant messaging client, wherein the instant messaging client is a client component installed in a user device;
wherein the system (100) is characterised in that it further includes:
i. an instant messaging intelligence platform for providing a list of contacts having similar interest with a user and suggesting rich content related to text messages inputted by the user, wherein the instant messaging intelligence platform is connected to the instant messaging client; and
ii. a knowledge based ontology (150) and Internet (160) connected to the instant messaging intelligence platform.
The system (100) as claimed in claim 1 , wherein the instant messaging intelligence platform comprises of:
i. a Chat Entry Box (110) to display the input data from user, wherein the Chat Entry Box (110) displays text messages between users;
ii. a Semantic Keyword Generator (120) to extract keywords from the text messages in the Chat Entry Box (110);
iii. a Rich Content Generator (130) to display a suggested content related to the text messages in the Chat Entry Box (110), wherein the suggested content is generated by using the knowledge based ontology (150); and
iv. a Semantic Match Maker (140) to provide a list of potential contacts having similar interest with a user of the instant messaging intelligence platform, wherein the list of potential contact is suggested based on the keywords extracted by the Semantic Keyword Generator (120).
3. The system (100) as claimed in claim 2, wherein the Rich Content Generator (130) includes a Term Frequency Calculator to determine the frequency of occurrence of the keywords used in the text messages in the Chat Entry Box (110). A method for instant messaging is characterised by the steps of:
a) receiving input data in the Chat Entry Box (110) from a user; b) extracting keywords based on the input data in the Chat Entry Box (110) by the Semantic Keyword Generator (120);
c) forwarding extracted keywords to the Rich Content Generator (130) and the Semantic Match Maker (140) by the Semantic Keyword Generator (120);
d) suggesting relevant rich content to the user by the Rich Content Generator (130) based on the extracted keyword; and e) matching similar interest contacts by the Semantic Match Maker (140) based on the keywords extracted by the Semantic Keyword Generator (120).
5. The method as claimed in claim 4, wherein extracting keywords based on input data from the user by the Semantic Keyword Generator (120) includes the steps of:
a) analysing textual entry in the Chat Entry Box (110);
b) assigning the textual entry to the text entry area;
c) dividing the textual entry to an array of texts;
d) identifying noun in the array of texts;
e) tagging the identified noun from the array of texts as keyword, f) validating the combination of nouns if there is adjacent noun; and g) tagging and forwarding the combination of nouns as keyword to the Rich Content Generator (130) and the Semantic Match Maker (140) if the combination of nouns is valid.
6. The method as claimed in claim 5, wherein extracting keywords based on input data from the user by the Semantic Keyword Generator (120) includes the step of returning empty string as the keyword if there is no adjacent noun identified or if the combination of nouns is invalid.
7. The method as claimed in claim 4, wherein suggesting the relevant rich content by the Rich Content Generator (130) includes the steps of:
a) receiving the extracted keyword by the rich Content Generator (130); b) sending the extracted keyword to the knowledge based ontology (160); c) categorising the results from the search into links, videos, images and keywords;
d) determining and assigning order of relevance of the frequency of occurrence of the extracted keywords in each result by the Term Frequency Calculator of the Rich Content Generator (130); and e) displaying the list of the relevant rich content ranked by relevance by the Rich Content Generator (130).
8. The method as claimed in claim 4, wherein matching similar interest contacts by the Semantic Match Maker (140) includes the steps of:
a) receiving the extracted keywords by the Semantic Match Maker (140); b) storing the extracted keywords as a topic of interest in the user profile; c) updating the topic of interest in the user profile if new topic of interest is been introduced;
d) comparing the user profile with the profile of other users and chat rooms by the Semantic Match Maker (130); and
e) displaying the profile of the listed contacts and chat rooms by the Semantic Match Maker (140).
PCT/MY2014/000177 2013-11-28 2014-06-12 A system and method for instant messaging platform WO2015080563A1 (en)

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