System and method for retrieving information related to targeted subjects

• US 20030101104A1
• Filed: 11/28/2001
• Published: 05/29/2003
• Est. Priority Date: 11/28/2001
• Status: Abandoned Application

• Current Assignee: Koninklijke Philips Electronics N.V. (Koninklijke Philips N.V.)
• Original Assignee: Koninklijke Philips Electronics N.V. (Koninklijke Philips N.V.)
• Inventors: Dimitrova, Nevenka, Agnihotri, Lalitha, Li, Dongge
• Application Number:
  US09/995,471
• Publication Number:
  US 20030101104A1
• Time in Patent Office: Days
• US Class Current: 705/27
• CPC Class Codes: G06F 16/735 Filtering based on additional data, e.g. user or group profiles
• CPC Class Codes: G06F 16/7834 using audio features
• CPC Class Codes: G06F 16/784 the detected or recognised objects being people
• CPC Class Codes: G06F 16/7844 using original textual content or text extracted from visual content or transcript of audio data
• CPC Class Codes: G06Q 30/0641 Shopping interfaces
• CPC Class Codes: H04N 21/23418 involving operations for analysing video streams, e.g. detecting features or characteristics television picture signal circuitry for scene change detection H04N5/147; filtering for image enhancement G06T5/00; methods or arrangements for recognising scenes G06V20/00; arrangements characterised by components specially adapted for monitoring, identification or recognition of video in broadcast systems H04H60/59
• CPC Class Codes: H04N 21/4394 involving operations for analysing the audio stream, e.g. detecting features or characteristics in audio streams arrangements characterised by components specially adapted for monitoring, identification or recognition of audio in broadcast systems H04H60/58
• CPC Class Codes: H04N 21/44008 involving operations for analysing video streams, e.g. detecting features or characteristics in the video stream arrangements characterised by components specially adapted for monitoring, identification or recognition of video in broadcast systems H04H60/59
• CPC Class Codes: H04N 21/4532 involving end-user characteristics, e.g. viewer profile, preferences monitoring of user activities for profile generation for accessing a video database G06F16/739; user profiles in network data switching protocols H04L67/306; processing of user preferences or user profiles in wireless networks H04W8/18
• CPC Class Codes: H04N 21/454 Content or additional data filtering, e.g. blocking advertisements
• CPC Class Codes: H04N 21/4663 involving probabilistic networks, e.g. Bayesian networks
• CPC Class Codes: H04N 21/84 Generation or processing of descriptive data, e.g. content descriptors systems specially adapted for using meta-information in broadcast systems H04H60/73
• CPC Class Codes: H04N 7/163 by receiver means only

Abstract

An information tracking device receives content data, such as a video or television signal from one or more information sources and analyzes the content data according to a query criteria to extract relevant stories. The query criteria utilizes a variety of information, such as but not limited to a user request, a user profile, and a knowledge base of known relationships. Using the query criteria, the information tracking device calculates a probability of a person or event occurring in the content data and spots and extracts stories accordingly. The results are index, ordered, and then displayed on a display device.

Claims

1. An information tracker, comprising:

a content analyzer comprising a memory for storing content data received from an information source and a processor for executing a set of machine-readable instructions for analyzing the content data according to query criteria;

an input device communicatively connected to the content analyzer for permitting a user to interact with the content analyzer; and

a display device communicatively connected to the content analyzer for displaying a result of analysis of the content data performed by the content analyzer;

wherein, according to the set of machine-readable instructions, the processor of the content analyzer analyzes the content data to extract and index one or more stories related to the query criteria.

2. The information tracker of claim 1, wherein the processor of the content analyzer uses the query criteria to spot a subject in the content data, extract one or more stories from the content data, resolve and inference names in the extracted one or more stories, and display a link to the extracted one or more stories on the display device.

3. The information tracker of claim 2, wherein, in addition to displaying the link to the extracted one or more stories, the content information about the subject to display one or more links to a shopping web-site, such that the user can purchase goods related to the subject.

4. The information tracker of claim 2, wherein the names in the extracted stories are resolved and inferenced using an ontology.

5. The information tracker of claim 2, wherein, if more than one story is extracted, the processor indexes the stories according to name, topic, and keyword.

6. The information tracker of claim 5, wherein the stories are further ordered based on a causality relationship.

7. The information tracker of claim 5, wherein the stories are further ordered based on a temporal relationship.

8. The information tracker of claim 1, wherein the query criteria includes a request input by the user through the input device and the processor analyzes the content data according to the request.

9. The information tracker of claim 8, wherein the content analyzer further comprises a user profile, which includes information about the user'"'"'s interests, and the query criteria includes the user profile.

10. The information tracker of claim 9, wherein the user profile is updated by integrating information in the request with existing information in the user profile.

11. The information tracker of claim 8, wherein the content analyzer further comprises a knowledge base, which includes a plurality of known relationships, and the processor analyzes the content data according to the knowledge base.

12. The information tracker of claim 11, wherein one type of the known relationships is a map of a known face to a name.

13. The information tracker of claim 11, wherein one type of the known relationships is a map of a known voice to a name.

14. The information tracker of claim 11, wherein one type of the known relationships is a map of a name to various related information.

15. The information tracker of claim 5, wherein the content analyzer further comprises:

a user profile, which includes information about the user'"'"'s interests;

a knowledge base which includes a plurality of known relationships including a map of known faces and voices to names and other related information; and

wherein the query criteria includes the user profile and the knowledge base.

16. The information tracker of claim 15, wherein a person spotting function of the machine-readable instructions extracts faces, speech, and text from the content data, makes a first match of known faces to the extracted faces, makes a second match of known voices to the extracted voices, scans the extracted text to make a third match to known names, and calculates a probability of a particular person being present in the content data based on the first, second, and third matches.

17. The information tracker of claim 1, wherein the content data is a video signal.

18. The information tracker of claim 17, wherein the information source is a cable television provider.

19. The information tracker of claim 17, wherein the information source is a satellite television provider.

20. The information tracker of claim 1, wherein the content data is an audio signal.

21. The information tracker of claim 20, wherein the information source is a radio station.

22. The information tracker of claim 1, wherein the content analyzer is communicatively connected to a second information source for providing access to additional content data, the additional content data being analyzed for relevant stories.

23. The information tracker of claim 22, wherein the additional content data is analyzed according to a first approach wherein terms are extracted from the query criteria and used to pose a search request of the second information source and a second approach wherein one or more sites provided by the second information are scanned for matching stories.

24. The information tracker of claim 23, wherein the intersection stories are those matching stories which were retrieved as a result of both the first and second approaches.

25. The information tracker of claim 22, wherein the relevant stories found in the additional content data are compared to find any intersection stories.

26. A method of retrieving information related to a targeted subject, the method comprising:

receiving a video source from an information source into a memory of a content analyzer;

analyzing the video to recognize persons and extract stories from the video source using a query criteria, the query criteria comprising a user profile and knowledge base stored in the content analyzer;

indexing the extracted stories according to a temporal and causal relationships; and

displaying of results of the analysis of the video source.

27. The method of claim 26, wherein the analyzing of the video source to recognize persons comprises extracting faces, speech, and text from the video source, making a first match of known faces to the extracted faces, making a second match of known voices to the extracted voices, scanning the extracted text to make a third match to known names, and calculating a probability of a particular person being present in the content data based on the first, second, and third matches.

28. The method of claim 26 wherein the analyzing of the video source to extract stories comprises segmenting the video source into visual, audio and textual components, fusing the information, segmenting and annotating the story internally, and inferencing the information.

29. The method of claim 26, wherein the indexing of the extracted stories comprises indexing the extracted stories alphabetically.

30. The method of claim 26, wherein the indexing of the extracted stories comprises indexing the extracted stories by topic.

31. The method of claim 26, wherein the indexing of the extracted stories comprises indexing the extracted stories according to keywords matching the query criteria.

32. The method of claim 26, wherein the indexing of the extracted stories comprises extracting a causality relationship.

33. The method of claim 26, wherein the indexing of the extracted stories comprises extracting a temporal relationship.

34. The method of claim 26, wherein the indexing of the extracted stories comprises indexing the extracted stories according to a pre-determined criteria, extracting a causality relationship, and extracting a temporal relationship, calculating a rating for each of the extracted stories from one or more characteristics of the extracted stories, and prioritizing the extracted stories.

35. The method of claim 34, further comprising creating a hyperlinked index to the extracted stories and storing the hyperlinked index.

36. A method of retrieving information related to a targeted subject, the method comprising:

receiving information from a user into a content analyzer, the information related to the user'"'"'s interests;

receiving first content data into the content analyzer;

analyzing the first content data to extract a story relevant to the information received from the user; and

displaying a link to the story so as to make the story accessible to the user.

37. The method of claim 36, further comprising accessing second content data and searching the second content data for relevant information.

38. The method of claim 36, wherein the content analyzer is centrally located and the user accesses the content analyzer via a communications network.

39. A information tracking retrieval system, comprising:

a centrally located content analyzer in communication with a storage device, the content analyzer being accessible to a plurality of users and information sources via a communications network, and the content analyzer being programmed with a set of machine-readable instructions to;

receive first content data into the content analyzer;

receive a request from at least one of the users;

in response to receipt of the request, analyze the first content data to extract one or more stories relevant to the request; and

provide access to the one or more stories.