Search (45 results, page 1 of 3)

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Abstract

Two probabilistic approaches to cross-lingual retrieval are in wide use today, those based on probabilistic models of relevance, as exemplified by INQUERY, and those based on language modeling. INQUERY, as a query net model, allows the easy incorporation of query operators, including a synonym operator, which has proven to be extremely useful in cross-language information retrieval (CLIR), in an approach often called structured query translation. In contrast, language models incorporate translation probabilities into a unified framework. We compare the two approaches on Arabic and Spanish data sets, using two kinds of bilingual dictionaries--one derived from a conventional dictionary, and one derived from a parallel corpus. We find that structured query processing gives slightly better results when queries are not expanded. On the other hand, when queries are expanded, language modeling gives better results, but only when using a probabilistic dictionary derived from a parallel corpus. We pursue two additional issues inherent in the comparison of structured query processing with language modeling. The first concerns query expansion, and the second is the role of translation probabilities. We compare conventional expansion techniques (pseudo-relevance feedback) with relevance modeling, a new IR approach which fits into the formal framework of language modeling. We find that relevance modeling and pseudo-relevance feedback achieve comparable levels of retrieval and that good translation probabilities confer a small but significant advantage.

Date

26.12.2007 20:22:11

Source

Information processing and management. 41(2005) no.3, S.457-474

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Abstract

Technical terms and proper names constitute a major problem in dictionary-based cross-language information retrieval (CLIR). However, technical terms and proper names in different languages often share the same Latin or Greek origin, being thus spelling variants of each other. In this paper we present a novel two-step fuzzy translation technique for cross-lingual spelling variants. In the first step, transformation rules are applied to source words to render them more similar to their target language equivalents. The rules are generated automatically using translation dictionaries as source data. In the second step, the intermediate forms obtained in the first step are translated into a target language using fuzzy matching. The effectiveness of the technique was evaluated empirically using five source languages and English as a target language. The two-step technique performed better, in some cases considerably better, than fuzzy matching alone. Even using the first step as such showed promising results.

Source

Information processing and management. 41(2005) no.4, S.859-872

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Date

26.12.2007 20:22:38

Source

Information processing and management. 41(2005) no.3, S.507-522

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Abstract

The CACAO Project (Cross-language Access to Catalogues and Online Libraries) has been designed to implement natural language processing and cross-language information retrieval techniques to provide cross-language access to information in libraries, a critical issue in the linguistically diverse European Union. This project report addresses two metadata-related challenges for the library community in this context: "false friends" (identical words having different meanings in different languages) and term ambiguity. The possible solutions involve enriching the metadata with attributes specifying language or the source authority file, or associating potential search terms to classes in a classification system. The European Library will evaluate an early implementation of this work in late 2008.

Source

Metadata for semantic and social applications : proceedings of the International Conference on Dublin Core and Metadata Applications, Berlin, 22 - 26 September 2008, DC 2008: Berlin, Germany / ed. by Jane Greenberg and Wolfgang Klas

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Source

Information processing and management. 36(2000) no.2, S.275-289

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Content

This paper explores the feasibility of developing mixed translations of the Dewey Decimal Classification (DDC system in countries/language groups where English enjoys wide use in academic and social discourse. A mixed translation uses existing DDC data in the vernacular plus additional data from the English-language full edition of the DDC to form a single mixed edition. Two approaches to mixed translations using Norwegian/English and Swedish/English DDC data are described, along with the design of a pilot study to evaluate use of a mixed translation as a classifier's tool.

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Abstract

For the sake of national security, very large volumes of data and information are generated and gathered daily. Much of this data and information is written in different languages, stored in different locations, and may be seemingly unconnected. Crosslingual semantic interoperability is a major challenge to generate an overview of this disparate data and information so that it can be analyzed, shared, searched, and summarized. The recent terrorist attacks and the tragic events of September 11, 2001 have prompted increased attention an national security and criminal analysis. Many Asian countries and cities, such as Japan, Taiwan, and Singapore, have been advised that they may become the next targets of terrorist attacks. Semantic interoperability has been a focus in digital library research. Traditional information retrieval (IR) approaches normally require a document to share some common keywords with the query. Generating the associations for the related terms between the two term spaces of users and documents is an important issue. The problem can be viewed as the creation of a thesaurus. Apart from this, terrorists and criminals may communicate through letters, e-mails, and faxes in languages other than English. The translation ambiguity significantly exacerbates the retrieval problem. The problem is expanded to crosslingual semantic interoperability. In this paper, we focus an the English/Chinese crosslingual semantic interoperability problem. However, the developed techniques are not limited to English and Chinese languages but can be applied to many other languages. English and Chinese are popular languages in the Asian region. Much information about national security or crime is communicated in these languages. An efficient automatically generated thesaurus between these languages is important to crosslingual information retrieval between English and Chinese languages. To facilitate crosslingual information retrieval, a corpus-based approach uses the term co-occurrence statistics in parallel or comparable corpora to construct a statistical translation model to cross the language boundary. In this paper, the text based approach to align English/Chinese Hong Kong Police press release documents from the Web is first presented. We also introduce an algorithmic approach to generate a robust knowledge base based an statistical correlation analysis of the semantics (knowledge) embedded in the bilingual press release corpus. The research output consisted of a thesaurus-like, semantic network knowledge base, which can aid in semanticsbased crosslingual information management and retrieval.

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Source

Information processing and management. 41(2005) no.3, S.433-456

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Abstract

While many websites aim at a large and linguistically diversified audience, they present their information mostly in the languages of larger speakers groups. Little is known about the effect on accessibility. We investigated the influence of a site's language offer on website access and search behaviour with two studies, and studied the interaction of language offers and domain knowledge. To achieve high ecological validity, we analysed data from a multilingual site's web-server logfile and from a questionnaire posted on it, and compared the behaviour of users who accessed the site in a non-native language to that of users who accessed it in their native language. Results from 277,809 user sessions and 165 international survey participants indicate that a website's languages may strongly reduce website access by users not supplied with information in their native language. Once inside a site, non-native speakers with high domain knowledge behave similarly to native speakers. However, non-native speakers' behaviour becomes language-sensitive when they have low domain knowledge.

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Abstract

The predominance of English-only online health information poses a serious challenge to nonEnglish speakers. To overcome this barrier, we incorporated cross-language information retrieval (CLIR) techniques into a fully functional prototype. It supports Spanish language searches over an English data set using a Spanish-English bilingual term list (BTL). The modular design allows for system and BTL growth and takes advantage of English-system enhancements. Language-based design decisions and implications for integrating non-English components with the existing monolingual architecture are presented. Algorithmic and BTL improvements are used to bring CUR retrieval scores in line with the monolingual values. After validating these changes, we conducted a failure analysis and error categorization for the worst performing queries. We conclude with a comprehensive discussion and directions for future work.

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Source

Information processing and management. 43(2007) no.1, S.47-64

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Source

Information processing and management. 41(2005) no.3, S.489-506

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Abstract

This paper examines whether a concept's hierarchical level affects the likelihood of its universality across schemes for knowledge representation and knowledge organization. Empirical data an equivalents are drawn from a bilingual thesaurus, a pair of biomedical vocabularies, and two ontologies. Conceptual equivalence across resources occurs significantly more often at the basic level than at subordinate or superordinate levels. Attempts to integrate knowledge representation or knowledge organization tools should concentrate an establishing equivalences at the basic level. 1. Rationale The degree of success attainable in the integration of multiple knowledge representation systems or knowledge organization schemes is constrained by limitations an the universality of human conceptual systems. For example, human languages do not all lexicalize the same set of concepts; nor do they structure (quasi-)equivalent concepts in the same relational patterns (Riesthuis, 2001). As a consequence, even multilingual thesauri designed from the outset from the perspective of multiple languages may routinely include situations where corresponding terms are not truly equivalent (Hudon, 1997, 2001). Intuitively, where inexactness and partialness in equivalence mappings across knowledge representation schemes and knowledge organizations schemes exist, a more difficult retrieval scenario arises than where equivalence mappings reflect full and exact conceptual matches. The question we address in this paper is whether a concept's hierarchical level af ects the likelihood of its universality/full equivalence across schemes for knowledge representation and knowledge organization. Cognitive science research has shown that one particular hierarchical level-called the basic level--enjoys a privileged status (Brown, 1958; Rosch et al., 1976). Our underlying hypothesis is that concepts at the basic level (e.g., apple, shoe, chair) are more likely to match across knowledge representation schemes and knowledge organization schemes than concepts at the superordinate (e.g., fruit, footwear, furniture) or subordinate (e.g., Granny Smith, sneaker, recliner) levels. This hypothesis is consistent with ethnobiological data showing that folk classifications of flora are more likely to agree at the basic level than at superordinate or subordinate levels (Berlin, 1992).

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Abstract

The growth in availability of multi-lingual data in all areas of the public and private sector is driving an increasing need for systems that facilitate access to multi-lingual resources. Cross-language Retrieval (CLR) technology is a means of addressing this need. A CLR system must address two main hurdles to effective cross-language retrieval. First, it must address the ambiguity that arises when trying to map the meaning of text across languages. That is, it must address both within-language ambiguity and cross-language ambiguity. Second, it has to incorporate multilingual resources that will enable it to perform the mapping across languages. The difficulty here is that there is a limited number of lexical resources and virtually none for some pairs of languages. This work focuses on a dictionary approach to addressing the problem of limited lexical resources. A dictionary approach is taken since bilingual dictionaries are more prevalent and simpler to apply than other resources. We show that a transitive translation approach, where a third language is employed as an interlingua between the source and target languages, is a viable means of performing CLR between languages for which no bilingual dictionary is available

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Abstract

For many years, the Web became an important media for the diffusion of multilingual resources. Linguistic differenees still form a major obstacle to scientific, cultural, and educational exchange. Besides this linguistic diversity, a multitude of databases and collections now contain documents in various formats, which may also adversely affect the retrieval process. This paper describes a research project aiming to verify the existing relations between two indexing approaches: traditional image indexing recommending the use of controlled vocabularies or free image indexing using uncontrolled vocabulary, and their respective performance for image retrieval, in a multilingual context. This research also compares image retrieval within two contexts: a monolingual context where the language of the query is the same as the indexing language; and a multilingual context where the language of the query is different from the indexing language. This research will indicate whether one of these indexing approaches surpasses the other, in terms of effectiveness, efficiency, and satisfaction of the image searchers. This paper presents the context and the problem statement of the research project. The experiment carried out is also described, as well as the data collection methods

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Abstract

In this paper we briefly sketch the dynamics of the linguistic paradigm in Information Retrieval (IR) and its adaptation to the Internet. The emergence of Natural Language Processing (NLP) techniques has been a major factor leading to this adaptation. These techniques and tools try to adapt to the current needs, i.e. retrieving information from documents written and indexed in a foreign language by using a native language query to express the information need. This process, known as cross-language IR (CLIR), is a field at the cross roads of both Machine Translation and IR. This field represents a real challenge to the IR community and will require a solid cooperation with the NLP community.

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Information processing and management. 43(2007) no.1, S.65-80

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Source

Information processing and management. 43(2007) no.2, S.488-502

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Source

Information processing and management. 42(2006) no.5, S.1203-1217

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Source

Information processing and management. 41(2005) no.3, S.415-432