Collecting training data using anomaly detection

• US 10,078,632 B2
• Filed: 03/12/2016
• Issued: 09/18/2018
• Est. Priority Date: 03/12/2016
• Status: Active Grant

• Current Assignee: International Business Machines Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: Harper, Devin R., Lakshmanan, Pawan K., Schoeninger, Gregory W., Turner, Elliot B.
• Primary Examiner(s): Colucci, Michael
• Application Number:
  US15/068,545
• Publication Number:
  US 20170262429A1
• Time in Patent Office: 920 Days
• Field of Search: 704 9, 725 46, 725116, 715273, 715230, 709203
• CPC Class Codes: G06F 16/3329 Natural language query formulation or dialogue systems
• CPC Class Codes: G06F 16/35 Clustering; Classification
• CPC Class Codes: G06F 40/253 Grammatical analysis; Style critique
• CPC Class Codes: G06F 40/289 Phrasal analysis, e.g. finite state techniques or chunking
• CPC Class Codes: G06F 40/40 Processing or translation of natural language natural language analysis G06F40/20; semantic analysis G06F40/30

Abstract

An approach is provided in which an information handling system detects a multi-entity co-occurrence anomaly within a set of documents that corresponds to an amount of times that a first entity and a second entity co-occur in the set of documents. The information handling system then determines that at least one of the documents includes a title having a verb that grammatically connects the first entity to the second entity. As such, the information handling system collects document segments from the set of documents that have the first entity, the second entity, and the connecting verb. In turn, the information handling system uses the collected document segments to train a relation-based classifier.

Claims

1. A method implemented by an information handling system that includes a memory and a processor, the method comprising:

identifying an amount of instances of a first entity and a second entity co-occurring within a set of documents, wherein the set of documents correspond to a time duration;

determining whether the amount of instances exceeds a threshold;

in response to determining that the amount of instances exceeds the threshold, identifying at least one title, corresponding to the set of documents, that comprises the first entity, the second entity, and at least one connecting verb that grammatically connects the first entity to the second entity;

in response to identifying the at least one title that comprises the first entity, the second entity, and at least one connecting verb, identifying a plurality of connecting verbs within the set of documents that each grammatically connects the first entity to the second entity, wherein the at least one connecting verb is included in the plurality of connecting verbs;

in response to identifying the plurality of connecting verbs, selecting a plurality of document segments within the set of documents that comprise the first entity, the second entity, and at least one of the plurality of connecting verbs;

storing the selected plurality of document segments in the memory; and

training a relation-based classifier using the stored plurality of document segments.

2. The method of claim 1 wherein the first entity is a first entity type and the second entity is a second entity type, and wherein both the first entity and the second entity are devoid of an entity name.

3. The method of claim 1 further comprising:

wherein each of the set of documents include a time stamp within the time duration.

4. The method of claim 1 further comprising:

selecting a set of relevant connecting verbs, from the plurality of connecting verbs, based upon an amount of each of the plurality of connecting verbs and their relevance; and

performing the collection of the plurality of document segments based upon the set of relevant connecting verbs.

5. The method of claim 4 wherein each of the plurality of connecting verbs form a subject-verb-object (SVO) relation with the first entity and the second entity.

6. The method of claim 1 wherein the information handling system is a question answer system, the method further comprising:

generating an alert in response to determining that the amount of instances exceeds the threshold, wherein the alert includes the first entity, the second entity, and the at least one connecting verb.

7. The method of claim 1 wherein the first entity and the second entity are selected from the group consisting of an entity type and an entity name.

8. An information handling system comprising:

one or more processors;

a memory coupled to at least one of the processors; and

a set of computer program instructions stored in the memory and executed by at least one of the processors in order to perform actions of;

identifying an amount of instances of a first entity and a second entity co-occurring within a set of documents, wherein the set of documents correspond to a time duration;

determining whether the amount of instances exceeds a threshold;

in response to determining that the amount of instances exceeds the threshold, identifying at least one title, corresponding to the set of documents, that comprises the first entity, the second entity, and at least one connecting verb that grammatically connects the first entity to the second entity;

in response to identifying the at least one title that comprises the first entity, the second entity, and at least one connecting verb, identifying a plurality of connecting verbs within the set of documents that each grammatically connects the first entity to the second entity, wherein the at least one connecting verb is included in the plurality of connecting verbs;

in response to identifying the plurality of connecting verbs, selecting a plurality of document segments within the set of documents that comprise the first entity, the second entity, and at least one of the plurality of connecting verbs;

storing the selected plurality of document segments in the memory; and

training a relation-based classifier using the stored plurality of document segments.

9. The information handling system of claim 8 wherein the first entity is a first entity type and the second entity is a second entity type, and wherein both the first entity and the second entity are devoid of an entity name.

10. The information handling system of claim 8 wherein at least one of the one or more processors perform additional actions comprising:

wherein each of the set of documents include a time stamp within the time duration.

11. The information handling system of claim 8 wherein at least one of the one or more processors perform additional actions comprising:

selecting a set of relevant connecting verbs, from the plurality of connecting verbs, based upon an amount of each of the plurality of connecting verbs and their relevance; and

performing the collection of the plurality of document segments based upon the set of relevant connecting verbs.

12. The information handling system of claim 11 wherein each of the plurality of connecting verbs form a subject-verb-object (SVO) relation with the first entity and the second entity.

13. The information handling system of claim 8 wherein the information handling system is a question answer system, and wherein at least one of the one or more processors perform additional actions comprising:

generating an alert in response to determining that the amount of instances exceeds the threshold, wherein the alert includes the first entity, the second entity, and the at least one connecting verb.

14. The information handling system of claim 8 wherein the first entity and the second entity are selected from the group consisting of an entity type and an entity name.

15. A computer program product stored in a computer readable storage medium, comprising computer program code that, when executed by an information handling system, causes the information handling system to perform actions comprising:

identifying an amount of instances of a first entity and a second entity co-occurring within a set of documents, wherein the set of documents correspond to a time duration;

determining whether the amount of instances exceeds a threshold;

in response to determining that the amount of instances exceeds the threshold, identifying at least one title, corresponding to the set of documents, that comprises the first entity, the second entity, and at least one connecting verb that grammatically connects the first entity to the second entity;

in response to identifying the at least one title that comprises the first entity, the second entity, and at least one connecting verb, identifying a plurality of connecting verbs within the set of documents that each grammatically connects the first entity to the second entity, wherein the at least one connecting verb is included in the plurality of connecting verbs;

in response to identifying the plurality of connecting verbs, selecting a plurality of document segments within the set of documents that comprise the first entity, the second entity, and at least one of the plurality of connecting verbs;

storing the selected plurality of document segments in the memory; and

training a relation-based classifier using the stored plurality of document segments.

16. The computer program product of claim 15 wherein the first entity is a first entity type and the second entity is a second entity type, and wherein both the first entity and the second entity are devoid of an entity name.

17. The computer program product of claim 15 wherein the information handling system performs additional actions comprising:

wherein each of the set of documents include a time stamp within the time duration.

18. The computer program product of claim 15 wherein the information handling system performs additional actions comprising:

selecting a set of relevant connecting verbs, from the plurality of connecting verbs, based upon an amount of each of the plurality of connecting verbs and their relevance; and

performing the collection of the plurality of document segments based upon the set of relevant connecting verbs.

19. The computer program product of claim 18 wherein each of the plurality of connecting verbs form a subject-verb-object (SVO) relation with the first entity and the second entity.

20. The computer program product of claim 15 wherein the information handling system is a question answer system, and wherein the information handling system performs additional actions comprising:

generating an alert in response to determining that the amount of instances exceeds the threshold, wherein the alert includes the first entity, the second entity, and the at least one connecting verb.