Entity metadata attached to multi-media surface forms

• US 10,009,297 B2
• Filed: 03/12/2015
• Issued: 06/26/2018
• Est. Priority Date: 03/12/2015
• Status: Active Grant

• Current Assignee: International Business Machines Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: Castelli, Vittorio, Florian, Radu, Sil, Avirup
• Primary Examiner(s): Hailu, Tadesse
• Application Number:
  US14/645,935
• Publication Number:
  US 20160267071A1
• Time in Patent Office: 1,202 Days
• CPC Class Codes: G06F 40/284 Lexical analysis, e.g. tokenisation or collocates
• CPC Class Codes: G06Q 10/10 Office automation; Time management
• CPC Class Codes: H04L 51/04 Real-time or near real-time messaging, e.g. instant messaging [IM]
• CPC Class Codes: H04L 51/08 Annexed information, e.g. attachments
• CPC Class Codes: H04L 67/10 in which an application is distributed across nodes in the network software deployment G06F8/60; multiprogramming arrangements G06F9/46

Abstract

A method, system, and/or computer program product displays related content on a user interface. An initial electronic document is analyzed to identify a mention in the initial electronic document. A mention descriptor of the mention in the initial electronic document is generated according to a context of the initial electronic document. The mention descriptor is mapped to a disambiguation identifier from a knowledge base that contains an entity related to the mention, where the disambiguation identifier identifies the entity within the knowledge base. The disambiguation identifier is associated with the initial electronic document, and is also associated with an entity metadata visualization panel. The disambiguation identifier is associated with the entity metadata visualization panel by mapping the entity metadata visualization panel to the disambiguation identifier. The entity metadata visualization panel is retrieved and displayed, on the user interface, as content related to the mention in the initial electronic document.

Claims

1. A method of displaying related content on a user interface, the method comprising:

analyzing, by one or more processors, an initial electronic document to identify a first mention in the initial electronic document;

generating, by one or more processors, a first mention descriptor of the first mention in the initial electronic document according to a context of the initial electronic document;

appending, by one or more processors, the first mention descriptor to the initial electronic document;

mapping, by one or more processors, the first mention descriptor from the initial electronic document to a disambiguation identifier from a knowledge base that contains a version of the first mention, wherein the disambiguation identifier is an entity within the knowledge base;

associating, by one or more processors, the disambiguation identifier with the initial electronic document;

locating, by one or more processors, the disambiguation identifier on an entity metadata visualization panel, wherein the disambiguation identifier was appended to the entity metadata visualization panel after mapping the entity metadata visualization panel to the disambiguation identifier from the knowledge base, and wherein the entity metadata visualization panel was mapped to the disambiguation identifier by mapping a second mention descriptor for a second mention in the entity metadata visualization panel to the disambiguation identifier;

retrieving, by one or more processors, the entity metadata visualization panel; and

displaying, on the user interface, the entity metadata visualization panel as related content that is related to the first mention in the initial electronic document.

2. The method of claim 1, wherein the initial electronic document is from a social media service, and wherein the method further comprises:

analyzing a frequency of the initial electronic document being viewed within predetermined time periods;

generating a trending graph of the frequency of the initial electronic document being viewed within the predetermined time periods; and

displaying, on the user interface, the trending graph.

3. The method of claim 2, wherein the social media service is a short messaging service.

4. The method of claim 2, wherein the social media service is a video sharing service.

5. The method of claim 1, further comprising:

performing a sentiment analysis on the initial electronic document, wherein the sentiment analysis identifies an emotion of a first author of the initial electronic document;

performing a sentiment analysis on the entity metadata visualization panel, wherein the sentiment analysis identifies an emotion of a second author of the entity metadata visualization panel;

generating a trending graph of the emotion of the first author and the emotion of the second author; and

displaying, on the user interface, the trending graph.

6. The method of claim 1, wherein the knowledge base contains multiple disambiguation identifiers, and wherein the method further comprises:

hierarchically categorizing the multiple disambiguation identifiers;

generating a graph of the hierarchically categorized disambiguation identifiers; and

displaying, on the user interface, the graph of the hierarchically categorized disambiguation identifiers.

7. The method of claim 1, further comprising:

performing an analysis of the entity metadata visualization panel to identify other topics presented in the entity metadata visualization panel;

generating a trending graph of the other topics presented in the entity metadata visualization panel; and

displaying, on the user interface, the trending graph.

8. The method of claim 1, wherein an entity tag identifies an entity as being either a person, an organization, or a geopolitical entity, and wherein the method further comprises:

appending an entity tag to the first mention descriptor appended to the initial electronic document; and

matching, by one or more processors, the entity tag from the first mention descriptor to an entity tag from the disambiguation identifier to further map the first mention descriptor to the disambiguation identifier.

9. The method of claim 1, wherein the first mention is not part of the entity metadata visualization panel.

10. The method of claim 1, wherein the first mention is a nominal term and the second mention is a pronominal phrase for a same entity.

11. The method of claim 1, wherein the initial electronic document is a first type of web log (blog) and the entity metadata visualization panel is a second type of blog, wherein the first type of blog is for a different subject than that of the second type of blog.

12. The method of claim 1, wherein the initial electronic document is a first webpage and the entity metadata visualization panel is a second webpage, wherein the first webpage is a different webpage than the second webpage.

13. A computer program product for displaying related content on a user interface, the computer program product comprising a computer readable storage medium having program code embodied therewith, the program code readable and executable by a processor to perform a method comprising:

analyzing an initial electronic document to identify a first mention in the initial electronic document;

generating a first mention descriptor of the first mention in the initial electronic document according to a context of the initial electronic document;

appending the first mention descriptor to the initial electronic document;

mapping the first mention descriptor from the initial electronic document to a disambiguation identifier from a knowledge base that contains a version of the first mention, wherein the disambiguation identifier is an entity within the knowledge base;

associating the disambiguation identifier with the initial electronic document;

locating the disambiguation identifier on an entity metadata visualization panel, wherein the disambiguation identifier was appended to the entity metadata visualization panel after mapping the entity metadata visualization panel to the disambiguation identifier from the knowledge base, and wherein the entity metadata visualization panel was mapped to the disambiguation identifier by mapping a second mention descriptor for a second mention in the entity metadata visualization panel to the disambiguation identifier;

retrieving the entity metadata visualization panel; and

displaying, on the user interface, the entity metadata visualization panel as related content that is related to the first mention in the initial electronic document.

14. The computer program product of claim 13, wherein the entity metadata visualization panel is from a social media service, and wherein the method further comprises:

displaying a trending graph of the entity metadata visualization panel on the user interface, wherein the trending graph describes a frequency of the entity metadata visualization panel being viewed within predetermined time periods.

15. The computer program product of claim 13, wherein the social media service is a short messaging service.

16. The computer program product of claim 13, wherein the social media service is a video sharing service.

17. The computer program product of claim 13, wherein the method further comprises:

performing a sentiment analysis on the initial electronic document, wherein the sentiment analysis identifies an emotion of a first author of the initial electronic document;

performing a sentiment analysis on the entity metadata visualization panel, wherein the sentiment analysis identifies an emotion of a second author of the entity metadata visualization panel;

generating a trending graph of the emotion of the first author and the emotion of the second author; and

displaying, on the user interface, the trending graph.

18. The computer program product of claim 13, wherein the knowledge base contains multiple disambiguation identifiers, and wherein the method further comprises:

hierarchically categorizing the multiple disambiguation identifiers;

generating a graph of the hierarchically categorized disambiguation identifiers; and

displaying, on the user interface, the graph of the hierarchically categorized disambiguation identifiers.

19. The computer program product of claim 13, wherein the method further comprises:

performing an analysis of the entity metadata visualization panel to identify other topics presented in the entity metadata visualization panel;

generating a trending graph of the other topics presented in the entity metadata visualization panel; and

displaying, on the user interface, the trending graph.

20. A computer system comprising:

a processor, a computer readable memory, and a non-transitory computer readable storage medium;

first program instructions to analyze an initial electronic document to identify a first mention in the initial electronic document;

second program instructions to generate a first mention descriptor of the first mention in the initial electronic document according to a context of the initial electronic document;

third program instructions to map the first mention descriptor to a disambiguation identifier from a knowledge base that contains a version of the first mention, wherein the disambiguation identifier identifies the mention within the knowledge base;

fourth program instructions to associate the disambiguation identifier with the initial electronic document;

fifth program instructions to locate the disambiguation identifier on an entity metadata visualization panel, wherein the disambiguation identifier was appended to the entity metadata visualization panel after mapping the entity metadata visualization panel to the disambiguation identifier from the knowledge base, and wherein the entity metadata visualization panel was mapped to the disambiguation identifier by mapping a second mention descriptor for a second mention in the entity metadata visualization panel to the disambiguation identifier;

sixth program instructions to retrieve the entity metadata visualization panel; and

seventh program instructions to display, on the user interface, the entity metadata visualization panel as related content that is related to the first mention in the initial electronic document; and

wherein

the first, second, third, fourth, fifth, sixth, and seventh program instructions are stored on the non-transitory computer readable storage medium for execution by one or more processors via the computer readable memory.