Adaptive Web Mining of Bilingual Lexicon for Query Translation

• US 20090182547A1
• Filed: 01/16/2008
• Published: 07/16/2009
• Est. Priority Date: 01/16/2008
• Status: Abandoned Application

• Current Assignee: Microsoft Technology Licensing LLC (Microsoft Corporation)
• Original Assignee: Microsoft Corporation
• Inventors: Niu, Cheng, Shi, Lei, Zhou, Ming
• Application Number:
  US12/015,491
• Publication Number:
  US 20090182547A1
• Time in Patent Office: Days
• US Class Current: 704/2
• CPC Class Codes: G06F 40/45 Example-based machine translation; Alignment

Abstract

Mining of translation pairs for cross-language translation uses a collective extraction model to exploit the similarity among the translation pairs and adaptively learn extraction patterns for each bilingual webpage. The process queries a web search engine by an initial term translation list to retrieve bilingual webpages containing translations, and crawls websites hosting the retreived bilingual webpages to retrieve additional bilingual webpages. The process then extracts additional translation pairs from the bilingual webpages retrieved by learning translation patterns of the bilingual webpages retrieved and adaptively extreacting translation pairs from the bilingual webpages using the learned translation patterns. More bilingual webpages may be acquired for additional website crawling and translation pair extracting by querying the web search engine by additional translation pairs.

Claims

1. A method for mining translation pairs for cross-language translation, the method comprising:

querying a web search engine by each translation pair of an initial term translation list to retrieve bilingual webpages containing translations;

crawling websites hosting the retrieved bilingual webpages to retrieve additional bilingual webpages;

extracting additional translation pairs from the bilingual webpages retrieved; and

querying the web search engine by each additional translation pairs to retrieve more bilingual webpages for additional website crawling and translation pair extracting.

2. The method as recited in claim 1, wherein extracting additional translation pairs from each bilingual web page comprises:

learning translation patterns of the bilingual webpages retrieved; and

adaptively extracting translation pairs from the bilingual webpages using the learned translation patterns.

3. The method as recited in claim 2, wherein learning translation patterns of the bilingual webpages retrieved comprises:

identifying webpage blocks containing translation pairs;

classifying the identified webpage blocks into at least two different classes;

identifying candidate translation patterns in each identified and classified webpage block; and

classifying identified candidate translation patterns into at least two different classes.

4. The method as recited in claim 2, wherein adaptively extracting translation pairs from the bilingual webpages comprises:

classifying each candidate translation pair using a plurality of feature functions.

5. The method as recited in claim 1, wherein extracting additional translation pairs from each bilingual web page comprises:

identifying a plurality of candidate translations in which a source language term form pairs with a set of corresponding target language terms; and

identifying a true candidate translation from the plurality of candidate translations using a translation classifier.

6. The method as recited in claim 5, wherein identifying the plurality of candidate translations comprises:

setting a continuous source language word sequence as a candidate source language term; and

identifying corresponding target language translation candidates.

7. The method as recited in claim 6, wherein identifying the corresponding target language translation candidates comprises:

selecting continuous target language word sequences which are within a context window surrounding the candidate source language term, and are started and ended with either a delimiter or a source language word; and

acquiring the corresponding target language translations from the continuous target language word sequences using a search snippet-based translation mining system.

8. The method as recited in claim 5, wherein identifying the true candidate translation from the plurality of candidate translations comprises:

classifying blocks of the retrieved webpages using a block classifier into at least a first category having many translations and the second category having few translations;

classifying candidate translation patterns using a pattern classifier into at least a first category having a strong pattern and a second category having a weak pattern; and

for each source language term, identifying a corresponding target language term using a translation extraction classifier based on results of the block classifier and the pattern classifier.

9. The method as recited in claim 8, wherein the block classifier and the pattern classifier are trained by performing acts comprising:

identifying salient webpage blocks and salient extraction patterns to facilitate a preliminary translation extraction; and

refining the block classifier and the pattern classifier based on results of the preliminary translation extraction to facilitate an improved translation extraction.

10. The method as recited in claim 8, wherein classifying blocks of the retrieved webpages using a block classifier comprises:

applying to each block a maximum entropy model based on feature functions including at least one of the following feature functions;

(i) a ratio of source language words in the block whose transliteration or dictionary-based translation is found in a context window;

(ii) a ratio of source language words in the block whose transliteration and dictionary-based translation cannot be found in the context window;

(iii) total number of source language words in the block;

(iv) a ratio of source language terms in the block whose snippet-based translation results can be found in the context window; and

(v) a translation direction tendency based on the number of source language words in the block which find their dictionary-based translation in their left context window, and the number of source language words in the block which find their dictionary-based translation in their left context window.

11. The method as recited in claim 8, wherein classifying candidate translation patterns using a pattern classifier comprises:

applying to each pattern a maximum entropy model based on feature functions including at least one of the following feature functions;

(i) among candidate translation pairs following the pattern, ratio of source language words whose transliteration or dictionary-based translation can be found in a context window;

(ii) among the candidate translation pairs following the pattern, ratio of source language words whose transliteration or dictionary-based translation cannot be found in the context window;

(iii) average length ratio of target language term to source language term; and

(iv) ratio of target language terms whose snippet-based translation results can be found in the context window.

12. The method as recited in claim 8, wherein identifying for each source language term a corresponding target language term comprises:

applying to each target language term a maximum entropy model based on feature functions including at least one of the following feature functions;

(i) classification label of the block containing the source language term and the target language term;

(ii) classification label of the extraction pattern for the source language term and the target language term;

(iii) whether the candidate pair can be confirmed by a snippet-based mining scheme;

(iv) ratio of source language words whose transliteration or dictionary-based translation can be found in the target language term;

(v) ratio of the source language words whose transliteration or dictionary-based translation cannot be found in the target language term;

(vi) ratio of the target language words whose transliteration or dictionary-based translation cannot be found in the source language term; and

(vii) ratio of the target language words whose transliteration or dictionary-based translation can be found in the source language term.

13. A method for extracting translation pairs from bilingual webpages, the method comprising:

learning webpage blocks containing translation pairs in the bilingual webpages and classifying the webpage blocks into at least two different block classes;

learning translation patterns in the bilingual webpages and classifying candidate translation patterns in the classified webpage blocks into at least two different pattern classes; and

adaptively extracting translation pairs from the bilingual webpages using the learned translation patterns.

14. The method as recited in claim 13, wherein adaptively extracting translation pairs from each bilingual web page comprises:

identifying a plurality of candidate translations in which a source language term form pairs with a set of corresponding target language terms; and

identifying a true candidate translation from the plurality of candidate translations using a translation classifier.

15. The method as recited in claim 13, wherein adaptively extracting translation pairs from each bilingual web page comprises:

setting a continuous source language word sequence as a candidate source language term;

selecting continuous target language word sequences which are within a context window surrounding the candidate source language term, and are started and ended with either a delimiter or a source language word; and

acquiring the corresponding target language translations from the continuous target language word sequences using a search snippet-based translation mining system.

16. The method as recited in claim 13, wherein adaptively extracting translation pairs from each bilingual web page comprises:

classifying blocks of the retrieved webpages using a block classifier into at least a first category having many translations and the second category having few translations;

classifying candidate translation patterns using a pattern classifier into at least a first category having a strong pattern and a second category having a weak pattern; and

for each source language term, identifying a corresponding target language term using a translation extraction classifier based on results of the block classifier and the pattern classifier.

17. The method as recited in claim 16, wherein the block classifier and the pattern classifier are trained by performing acts comprising:

identifying salient webpage blocks and extraction patterns to facilitate a preliminary translation extraction; and

refining the block classifier and the pattern classifier based on results of the preliminary translation extraction to facilitate an improved translation extraction.

18. The method as recited in claim 16, wherein identifying for each source language term a corresponding target language term comprises:

applying to each target language term a maximum entropy model based on feature functions including at least one of the following feature functions;

(i) a classification label of a webpage block containing the source language term and the target language term;

(ii) a classification label of an extraction pattern for the source language term and the target language term;

(iii) whether the candidate pair can be confirmed by a snippet-based mining scheme;

(iv) ratio of source language words whose transliteration or dictionary-based translation can be found in the target language term;

(v) ratio of the source language words whose transliteration or dictionary-based translation cannot be found in the target language term;

(vi) ratio of the target language words whose transliteration or dictionary-based translation cannot be found in the source language term; and

(vii) ratio of the target language words whose transliteration or dictionary-based translation can be found in the source language term.

19. One or more computer readable media having stored thereupon a plurality of instructions that, when executed by a processor, causes the processor to:

query a web search engine by each translation pair of an initial term translation list to retrieve bilingual webpages containing translations;

crawl websites hosting the retrieved bilingual webpages to retrieve additional bilingual webpages;

extract additional translation pairs from the bilingual webpages retrieved; and

query the web search engine by each additional translation pairs to retrieve more bilingual webpages for additional website crawling and translation pair extracting.

20. The computer readable media as recited in claim 19, wherein in order to extract additional translation pairs from each bilingual web page, the plurality of instructions, when executed by a processor, causes the processor to:

learn translation patterns of the bilingual webpages retrieved; and

adaptively extract translation pairs from the bilingual webpages using the learned translation patterns.