Search (49 results, page 3 of 3)

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Date

26.12.2007 20:22:11

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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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Abstract

In this paper we are concerned with the type of services that send periodic news selections to subscribers of a digital newspaper by means of electronic mail. The aims are to study the influence of categorisation in information retrieval and in digital newspapers, different models to solve problems of bilingualism in digital information services and to analyse the evaluation in information filtering and personalisation in information agents. Hermes is a multilingual system for the personalisation of news services which allows integration and categorisation of information in two languages. In order to customise information for each user, Hermes provides the means for representing a user interests homogeneously across the operating languages of the system. A simple system is applied to train automatically a dynamic news item classifier for both languages, by taking the Yahoo set of categories as reference framework and using the web pages classified under them as training collection. Traditional evaluation methods have been applied and their shortcomings for the present endeavour have been noted.

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Abstract

Information retrieval systems' ability to retrieve highly relevant documents has become more and more important in the age of extremely large collections, such as the World Wide Web (WWW). The authors' aim was to find out how corpus-based cross-language information retrieval (CLIR) manages in retrieving highly relevant documents. They created a Finnish-Swedish comparable corpus from two loosely related document collections and used it as a source of knowledge for query translation. Finnish test queries were translated into Swedish and run against a Swedish test collection. Graded relevance assessments were used in evaluating the results and three relevance criterion levels-liberal, regular, and stringent-were applied. The runs were also evaluated with generalized recall and precision, which weight the retrieved documents according to their relevance level. The performance of the Comparable Corpus Translation system (COCOT) was compared to that of a dictionarybased query translation program; the two translation methods were also combined. The results indicate that corpus-based CUR performs particularly well with highly relevant documents. In average precision, COCOT even matched the monolingual baseline on the highest relevance level. The performance of the different query translation methods was further analyzed by finding out reasons for poor rankings of highly relevant documents.

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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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Date

22. 4.2003 12:09:10

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Date

22. 4.2003 12:05:56

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Abstract

Introduction Multilingualism has long been an issue that have been discussed and debated at ELAG conferences. Members of ELAG have generally considered the role of automation as an important factor in the development of multilingual subject access solutions. It is quite fitting that in the context of this year's theme of "Cross language applications and the web" that the latest development of the MACS project be presented. As the title indicates, this presentation will focus an the latest development of the Link management Interface (LMI) which is the pivotal tool of the MACS multilingual subject access solution. It will update the presentation given by Genevieve ClavelMerrin at last year's ELAG 2002 Conference in Rome. That presentation gave a thorough description of the work that had been undertaken since 1997. In particular, G. Clavel-Merrin described the development of the MACS prototype in which the mechanisms for the establishment and management of links between subject heading languages (SHLs) and the user search interface had been implemented.

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Abstract

The proper handling of acronyms plays a crucial role in medical texts, e.g. in patient records, as well as in scientific literature. Chapter six presents an approach, in which acronyms are automatically acquired from (bio-) medical literature. Furthermore, acronyms and their definitions in different languages are linked to each other using the MorphoSaurus text processing system. Automatic word sense disambiguation is still one of the most challenging tasks in Natural Language Processing. In Chapter seven, cross-lingual considerations lead to a new methodology for automatic disambiguation applied to subwords. Beginning with Chapter eight, a series of applications based onMorphoSaurus are introduced. Firstly, the implementation of the subword approach within a crosslanguage information retrieval setting for the medical domain is described and evaluated on standard test document collections. In Chapter nine, this methodology is extended to multilingual information retrieval in the Web, for which user queries are translated into target languages based on the segmentation into subwords and their interlingual mappings. The cross-lingual, automatic assignment of document descriptors to documents is the topic of Chapter ten. A large-scale evaluation of a heuristic, as well as a statistical algorithm is carried out using a prominent medical thesaurus as a controlled vocabulary. In Chapter eleven, it will be shown how MorphoSaurus can be used to map monolingual, lexical resources across different languages. As a result, a large multilingual medical lexicon with high coverage and complete lexical information is built and evaluated against a comparable, already available and commonly used lexical repository for the medical domain. Chapter twelve sketches a few applications based on MorphoSaurus. The generality and applicability of the subword approach to other domains is outlined, and proof-of-concepts in real-world scenarios are presented. Finally, Chapter thirteen recapitulates the most important aspects of MorphoSaurus and the potential benefit of its employment in medical information systems is carefully assessed, both for medical experts in their everyday life, but also with regard to health care consumers and their existential information needs.