Bootstrapping dictionaries for cross-language information retrieval

Markó, Kornél G.; Schulz, Stefan; Medelyan, Olena; Hahn, Udo

doi:10.1145/1076034.1076124

Cited by 14 publications

(12 citation statements)

References 19 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…A variety of distributional models have been used for this task, including Latent Semantic Analysis [Dumais et al 1996] and topic models [De Smet and Moens 2009]. Query translation has been shown to contribute to information retrieval in related languages (translations from Portuguese, German, Spanish and Swedish to English in Markó et al [2005]) as well as unrelated languages (from Japanese to English in Sadat et al [2003]). …”

Section: Related Workmentioning

confidence: 99%

Semantic relations in bilingual lexicons

Peirsman

Padó

2008

ACM Trans. Speech Lang. Process.

View full text Add to dashboard Cite

Bilingual lexicons, essential to many NLP applications, can be constructed automatically on the basis of parallel or comparable corpora. In this article, we make two contributions to their induction from comparable corpora. The first one concerns the creation of these lexicons. We show that seed lexicons can be improved by adding a bootstrapping procedure that uses cross-lingual distributional similarity. The second contribution concerns the evaluation of bilingual lexicons. It is generally based on translation lexicons, which corresponds to the implicit assumption that (cross-lingual) synonymy is the semantic relation of primary interest, even though other semantic relations like (cross-lingual) hyponymy or cohyponymy make up a considerable portion of translation pair candidates proposed by distributional methods.We argue that the focus on synonymy is an oversimplification and that many applications can profit from the inclusion of other semantic relations. We study what effect these semantic relations have on two crosslingual tasks: the cross-lingual projection of polarity scores and the cross-lingual modeling of selectional preferences. We find that the presence of non-synonymous semantic relations may negatively affect the former of these tasks, but benefit the latter.

show abstract

Section: Related Workmentioning

confidence: 99%

Semantic relations in bilingual lexicons

Peirsman

Padó

2008

ACM Trans. Speech Lang. Process.

View full text Add to dashboard Cite

show abstract

“…Finally, from a more practical point of view, we believe it would be interesting to use n-gram based translation for supporting the generation process of multilingual thesaurus for technical domains, as in the case of MorphoSaurus (Schulz et al, 2006) in Medicine, and its application to CLIR tasks (Markó et al, 2005). Twitter and other microblogging services will deserve special attention since it is a very noisy multilingual environment, for which specialized linguistic resources are still very scarce, particularly for nonEnglish languages.…”

Section: Discussionmentioning

confidence: 99%

On the feasibility of character n-grams pseudo-translation for Cross-Language Information Retrieval tasks

Vilares

Alonso

et al. 2016

Computer Speech & Language

View full text Add to dashboard Cite

The field of Cross-Language Information Retrieval relates techniques close to both the Machine Translation and Information Retrieval fields, although in a context involving characteristics of its own. The present study looks to widen our knowledge about the effectiveness and applicability to that field of nonclassical translation mechanisms that work at character n-gram level. For the purpose of this study, an n-gram based system of this type has been developed. This system requires only a bilingual machine-readable dictionary of n-grams, automatically generated from parallel corpora, which serves to translate queries previously n-grammed in the source language. n-Gramming is then used as an approximate string matching technique to perform monolingual text retrieval on the set of n-grammed documents in the target language.The tests for this work have been performed on CLEF collections for seven European languages, taking English as the target language. The performance attained, close to the upper baseline, confirms the validity of character n-gram based approaches for Cross Language Information Retrieval tasks, both for indexing-retrieval and translation purposes, these not being tied to a given implementation.

show abstract

“…The MorphoSaurus system [4,5,10,11] maps the content of domain-specific texts to a concept-like interlingua. This entails a simplification and standardization of document source and user queries in order to facilitate the retrieval of documents in multilingual collections.…”

Section: The Morphosaurus System 21 Subwords As Atomic Meaning Identmentioning

confidence: 99%

“…Moreover, spelling and syntax rules are not always respected. Due to these peculiarities, current information retrieval approaches that are usually based on simple comparison of entire words are inappropriate because they produce results that are incomplete, inaccurate, or outside the desired scope [4].…”

Section: Introductionmentioning

confidence: 99%