Experiments in multilingual information retrieval using the SPIDER system

Sheridan, Paraic; Ballerini, Jean Paul

doi:10.1145/243199.243213

Cited by 135 publications

(71 citation statements)

References 10 publications

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“…One approach to accomplish this is with query expansion or using parallel corpora (e.g. [4,5]). In the first step of Sheridan et al [5], the best matching documents in the source language are retrieved.…”

Section: Related Workmentioning

confidence: 99%

WikiTranslate: Query Translation for Cross-Lingual Information Retrieval Using Only Wikipedia

Nguyen

Overwijk

Hauff

et al. 2009

Lecture Notes in Computer Science

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Abstract. This paper presents WikiTranslate, a system which performs query translation for cross-lingual information retrieval (CLIR) using only Wikipedia to obtain translations. Queries are mapped to Wikipedia concepts and the corresponding translations of these concepts in the target language are used to create the final query. WikiTranslate is evaluated by searching with topics formulated in Dutch, French and Spanish in an English data collection. The system achieved a performance of 67% compared to the monolingual baseline.

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Section: Related Workmentioning

confidence: 99%

WikiTranslate: Query Translation for Cross-Lingual Information Retrieval Using Only Wikipedia

Nguyen

Overwijk

Hauff

et al. 2009

Lecture Notes in Computer Science

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“…1 In such a case, our approach is closer in spirit to that of Sheridan and Ballerini [15] where the retrieval process consists of two retrieval steps. First, the best matching documents in the source language are retrieved.…”

Section: Related Workmentioning

confidence: 98%

Cross-lingual relevance models

Lavrenko

Choquette

Croft

2002

Proceedings of the 25th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval

148

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We propose a formal model of Cross-Language Information Retrieval that does not rely on either query translation or document translation. Our approach leverages recent advances in language modeling to directly estimate an accurate topic model in the target language, starting with a query in the source language. The model integrates popular techniques of disambiguation and query expansion in a unified formal framework. We describe how the topic model can be estimated with either a parallel corpus or a dictionary. We test the framework by constructing Chinese topic models from English queries and using them in the CLIR task of TREC9. The model achieves performance around 95% of the strong mono-lingual baseline in terms of average precision. In initial precision, our model outperforms the monolingual baseline by 20%. The main contribution of this work is the unified formal model which integrates techniques that are essential for effective Cross-Language Retrieval.

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“…Most of the research on the automatic creation of comparable corpora has involved established research corpora, such as the collections of TREC and CLEF conferences (Sheridan and Ballerini, 1996;Braschler and Schäuble, 1998). Surprisingly few studies exist on the acquisition of such corpora from the Web.…”

Section: Previous Workmentioning

confidence: 99%

“…A parallel corpus consists of document pairs that are more or less exact translations of each other. In a comparable corpus, the document pairs are not exact translations but have similar vocabulary (Sheridan and Ballerini, 1996). The aligned documents can be, e.g., accounts of the same news event written independently in different countries.…”

Section: Introductionmentioning

confidence: 99%

Focused web crawling in the acquisition of comparable corpora

et al. 2008

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CLIR resources, such as dictionaries and parallel corpora, are scarce for special domains. Obtaining comparable corpora automatically for such domains could be an answer to this problem. The Web, with its vast volumes of data, offers a natural source for this. We experimented with focused crawling as a means to acquire comparable corpora in the genomics domain. The acquired corpora were used to statistically translate domainspecific words. The same words were also translated using a high-quality, but non-genomics-related parallel corpus, which fared considerably worse. We also evaluated our system with standard IR experiments, combining statistical translation using the Web corpora with dictionary-based translation. The results showed improvement over pure dictionary-based translation. Therefore, mining the Web for comparable corpora seems promising.

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Experiments in multilingual information retrieval using the SPIDER system

Abstract: We introducea new approach to multilingual information retrieval based on the use of thesaurus-based query expansion techniques applied over a collection of comparable multilingual documents. This approach has been built into the SPI-

Cited by 135 publications

References 10 publications

WikiTranslate: Query Translation for Cross-Lingual Information Retrieval Using Only Wikipedia

WikiTranslate: Query Translation for Cross-Lingual Information Retrieval Using Only Wikipedia

Cross-lingual relevance models

Focused web crawling in the acquisition of comparable corpora

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