SEMANTIC REFINING OF CROSS-LINGUAL INFORMATION RETRIEVAL RESULTS

• US 20150199339A1
• Filed: 05/13/2014
• Published: 07/16/2015
• Est. Priority Date: 01/14/2014
• Status: Abandoned Application

• Current Assignee: Xerox Corporation (Xerox Holdings Corp.)
• Original Assignee: Xerox Corporation (Xerox Holdings Corp.)
• Inventors: MIRKIN, Shachar, LAGOS, Nikolaos, CALAPODESCU, loan
• Application Number:
  US14/276,252
• Publication Number:
  US 20150199339A1
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G06F 16/3337 Translation of the query language, e.g. Chinese to English
• CPC Class Codes: G06F 40/45 Example-based machine translation; Alignment
• CPC Class Codes: G06F 40/58 Use of machine translation, e.g. for multi-lingual retrieval, for server-side translation for client devices or for real-time translation

Abstract

A method for cross language information retrieval includes receiving an input query which includes at least one word in a source language and translating the input query from the source language to a target language to provide a set of translated queries. A set of documents is retrieved from a document collection based on the translated queries. The retrieved documents are translated back into the source language to generate a set of translated documents. An entailment relationship between each of the translated documents and the input query is assessed. The set of translated documents is refined, based on the assessment of the entailment relationship. A subset (or all) of the refined set of translated documents, and/or the target documents to which the translated documents in the subset correspond, is output.

Claims

1. A method for cross language information retrieval comprising:

receiving an input query which includes at least one word in a source language;

translating the input query from the source language to a target language to provide a set of translated queries;

retrieving documents from a document collection based on the translated queries;

translating at least a part of the retrieved documents into the source language to generate a set of translated documents;

assessing an entailment relationship between each of the translated documents and the input query;

refining the set of translated documents based on the assessment of the entailment relationship; and

outputting at least a subset of the refined set of translated documents or the target documents to which the translated documents in the subset correspond;

wherein at least one of the translating the input query, retrieving documents, translating the retrieved documents, assessing the entailment relationship, and refining the set of translated documents is performed with a computer processor.

2. The method of claim 1, wherein the refining of the set of translated documents comprises at least one of:

retaining only those translated documents for which entailment is found; and

ranking the translated documents based on an entailment score.

3. The method of claim 2, wherein the refining comprises removing documents from the set of translated documents that do not meet a threshold entailment score and ranking the remaining documents based on an entailment score.

4. The method of claim 3, wherein the ranking of the documents is also based on a retrieval score for the corresponding retrieved documents.

5. The method of claim 1, wherein the outputting at least a subset of the refined set of translated documents comprises displaying a part of at least some of the documents which led to a finding of textual entailment.

6. The method of claim 1, wherein the translating the input query from the source language to a target language comprises translating the input query to generate a set of candidate translations and from the candidate translations identifying a subset of the best candidate translations as the set of translated queries.

7. The method of claim 1, wherein the assessing of the entailment relationship comprises applying a set of textual entailment rules for identifying pairs of entailing and entailed text segments in the document input query, respectively.

8. The method of claim 7, wherein entailing text segment in the query comprises the entire query.

9. The method of claim 7, wherein the applying of the set of textual entailment rules comprises applying rules selected from the group consisting of:

lexical rules that identify one or more of synonymy, hypernymy, and meronymy between arguments of an entailing text segment and an entailed text segment, lexico-syntactic rules that capture relations between a pair of predicate-argument tuples of an entailing text segment and an entailed text segment, and combinations thereof.

10. The method of claim 1, wherein the set of translated queries comprises at least five translated queries.

11. The method of claim 1, wherein the set of translated queries comprises at most, a predetermined number of translated queries.

12. The method of claim 1, wherein the set of retrieved documents comprises at least five retrieved documents.

13. The method of claim 1, wherein the set of retrieved documents comprises at most, a predetermined number of retrieved documents.

14. A computer program product comprising a non-transitory recording medium storing instructions, which when executed on a computer, causes the computer to perform the method of claim 1.

15. A system for performing the method of claim 1 comprising memory which stores instructions for performing the method of claim 1 and a processor in communication with the memory for executing the instructions.

16. A system for cross language information retrieval comprising:

a first machine translation component for translating an input query from a source language to a target language to provide a set of translated queries;

a retrieval component for retrieving documents from an associated document collection based on the translated queries;

a second machine translation component for translating the retrieved documents into the source language to generate a set of translated documents;

an entailment component for assessing an entailment relationship between each of the translated documents and the input query;

a refinement component for refining the set of translated documents based on the assessment of the entailment relationship; and

a processor which implements the first and second machine translation components, retrieval component, entailment component, and refinement component.

17. The system of claim 16, wherein the first machine translation component comprises a first statistical machine translation component and the second machine translation component comprises a second statistical machine translation component.

18. The system of claim 16, wherein the retrieval component uses a service for retrieving the documents from an associated document collection to which the retrieval component does not have access;

19. A method for cross language information retrieval comprising:

receiving an input query which includes at least one word in a source language;

translating the input query from the source language to a target language to provide a set of translated queries;

retrieving documents from a document collection based on the translated queries;

optionally, translating the retrieved documents into the source language to generate a set of translated documents;

assessing an entailment relationship between each of the translated documents and the input query or between each of the untranslated retrieved documents and the input query;

refining the set of translated or untranslated documents based on the assessment of the entailment relationship, the refining comprising at least one of;

retaining only those documents for which an entailment relationship is found; and

ranking the documents based on an entailment score; and

providing for a user to review documents in the refined set of translated documents or corresponding untranslated documents,

wherein at least one of the translating the input query, retrieving documents, assessing the entailment relationship, and refining the set of translated documents is performed with a computer processor.

20. A computer program product comprising a non-transitory recording medium storing instructions, which when executed on a computer causes the computer to perform the method of claim 19.