Term disambiguation techniques based on target document collection for cross-language information retrieval: An empirical comparison of performance between techniques

Dictionary-based query translation for cross-language information retrieval often yields various translation candidates having different meanings for a source term in the query. This paper examines methods for solving the ambiguity of translations based on only the target document collections. First, we discuss two kinds of disambiguation technique: (1) one is a method using term co-occurrence statistics in the collection, and (2) a technique based on pseudo-relevance feedback. Next, these techniques are empirically compared using the CLEF 2003 test collection for German to Italian bilingual searches, which are executed by using English language as a pivot. The experiments showed that a variation of term co-occurrence based techniques, in which the best sequence algorithm for selecting translations is used with the Cosine coefficient, is dominant, and that the PRF method shows comparable high search performance, although statistical tests did not sufficiently support these conclusions. Furthermore, we repeat the same experiments for the case of French to Italian (pivot) and English to Italian (non-pivot) searches on the same CLEF 2003 test collection in order to verity our findings. Again, similar results were observed except that the Dice coefficient outperforms slightly the Cosine coefficient in the case of disambiguation based on term co-occurrence for English to Italian searches.

[1]  Gregory Grefenstette,et al.  Cross-Language Information Retrieval , 1998, The Springer International Series on Information Retrieval.

[2]  Noriko Kando,et al.  Two-Stage Refinement of Query Translation in a Pivot Language Approach to Cross-Lingual Information Retrieval: An Experiment at CLEF 2003 , 2003, CLEF.

[3]  M. F. Porter,et al.  An algorithm for suffix stripping , 1997 .

[4]  W. Bruce Croft,et al.  Evaluation of an inference network-based retrieval model , 1991, TOIS.

[5]  Christof Monz,et al.  Iterative translation disambiguation for cross-language information retrieval , 2005, SIGIR '05.

[6]  Noriko Kando,et al.  NTCIR workshop : proceedings of the first NTCIR workshop on research in Japanese text retrieval and term recognition , 1999 .

[7]  Hsin-Hsi Chen,et al.  Integrating Query Translation and Document Translation in a Cross-language Information Retrieval System , 1998, AMTA.

[8]  Gregory Grefenstette,et al.  Resolving Translation Ambiguity using Monolingual Corpora. A Report on Clairvoyance CLEF-2002 Experiments , 2002, CLEF.

[9]  Mohand Boughanem,et al.  Investigation on Disambiguation in CLIR: Aligned Corpus and Bi-directional Translation-Based Strategies , 2001, CLEF.

[10]  Stephen E. Robertson,et al.  Okapi at TREC-3 , 1994, TREC.

[11]  Mohand Boughanem,et al.  Mercure at CLEF-1 , 2000, CLEF.

[12]  Kenneth Ward Church,et al.  Word Association Norms, Mutual Information, and Lexicography , 1989, ACL.

[13]  Mark W. Davis,et al.  On The Effective Use of Large Parallel Corpora in Cross-Language Text Retrieval , 1998 .

[14]  W. Bruce Croft,et al.  Phrasal translation and query expansion techniques for cross-language information retrieval , 1997, SIGIR '97.

[15]  Mirna Adriani.  Using Statistical Term Similarity for Sense Disambiguation in Cross-Language Information Retrieval , 2004, Information Retrieval.

[16]  Jianfeng Gao,et al.  Resolving query translation ambiguity using a decaying co-occurrence model and syntactic dependence relations , 2002, SIGIR '02.

[17]  Kazuaki Kishida,et al.  Technical issues of cross-language information retrieval: a review , 2005, Inf. Process. Manag..

[18]  Mark W. Davis,et al.  New Experiments In Cross-Language Text Retrieval At NMSU's Computing Research Lab , 1996, TREC.

[19]  Hsin-Hsi Chen,et al.  Description of the NTU Japanese-English Cross-Lingual Information Retrieval System , 1999, NTCIR.

[20]  Ari Pirkola,et al.  The effects of query structure and dictionary setups in dictionary-based cross-language information retrieval , 1998, SIGIR '98.

[21]  Changning Huang,et al.  Improving query translation for cross-language information retrieval using statistical models , 2001, SIGIR '01.

[22]  Masatoshi Yoshikawa,et al.  Query term disambiguation for Web cross-language information retrieval using a search engine , 2000, IRAL '00.

[23]  Yamabana Kiyoshi,et al.  A Language Conversion Front-End for Cross-Language Information Retrieval , 1998, SIGIR 1998.

[24]  W. Bruce Croft,et al.  Resolving ambiguity for cross-language retrieval , 1998, SIGIR '98.

[25]  Yi Liu,et al.  A maximum coherence model for dictionary-based cross-language information retrieval , 2005, SIGIR '05.

[26]  Mirna Adriani,et al.  Ambiguity Problem in Multilingual Information Retrieval , 2000, CLEF.

[27]  Carol Peters,et al.  CLEF 2003 Methodology and Metrics , 2003, CLEF.

[28]  Sung-Hyon Myaeng,et al.  Using Mutual Information to Resolve Query Translation Ambiguities and Query Term Weighting , 1999, ACL.