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Content

Enthält die Beiträge: GREFENSTETTE, G.: The Problem of Cross-Language Information Retrieval; DAVIS, M.W.: On the Effective Use of Large Parallel Corpora in Cross-Language Text Retrieval; BALLESTEROS, L. u. W.B. CROFT: Statistical Methods for Cross-Language Information Retrieval; Distributed Cross-Lingual Information Retrieval; Automatic Cross-Language Information Retrieval Using Latent Semantic Indexing; EVANS, D.A. u.a.: Mapping Vocabularies Using Latent Semantics; PICCHI, E. u. C. PETERS: Cross-Language Information Retrieval: A System for Comparable Corpus Querying; YAMABANA, K. u.a.: A Language Conversion Front-End for Cross-Language Information Retrieval; GACHOT, D.A. u.a.: The Systran NLP Browser: An Application of Machine Translation Technology in Cross-Language Information Retrieval; HULL, D.: A Weighted Boolean Model for Cross-Language Text Retrieval; SHERIDAN, P. u.a. Building a Large Multilingual Test Collection from Comparable News Documents; OARD; D.W. u. B.J. DORR: Evaluating Cross-Language Text Filtering Effectiveness

Editor

Grefenstette, G.

Footnote

Christian Fluhr at al (DIST/SMTI, France) outline the EMIR (European Multilingual Information Retrieval) and ESPRIT projects. They found that using SYSTRAN to machine translate queries and to access material from various multilingual databases produced less relevant results than a method referred to as 'multilingual reformulation' (the mechanics of which are only hinted at). An interesting technique is Latent Semantic Indexing (LSI), described by Michael Littman et al (Brown University) and, most clearly, by David Evans et al (Carnegie Mellon University). LSI involves creating matrices of documents and the terms they contain and 'fitting' related documents into a reduced matrix space. This effectively allows queries to be mapped onto a common semantic representation of the documents. Eugenio Picchi and Carol Peters (Pisa) report on a procedure to create links between translation equivalents in an Italian-English parallel corpus. The links are used to construct parallel linguistic contexts in real-time for any term or combination of terms that is being searched for in either language. Their interest is primarily lexicographic but they plan to apply the same procedure to comparable corpora, i.e. to texts which are not translations of each other but which share the same domain. Kiyoshi Yamabana et al (NEC, Japan) address the issue of how to disambiguate between alternative translations of query terms. Their DMAX (double maximise) method looks at co-occurrence frequencies between both source language words and target language words in order to arrive at the most probable translation. The statistical data for the decision are derived, not from the translation texts but independently from monolingual corpora in each language. An interactive user interface allows the user to influence the selection of terms during the matching process. Denis Gachot et al (SYSTRAN) describe the SYSTRAN NLP browser, a prototype tool which collects parsing information derived from a text or corpus previously translated with SYSTRAN. The user enters queries into the browser in either a structured or free form and receives grammatical and lexical information about the source text and/or its translation.

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Editor

Byrum, J.D. u. O. Madison

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Editor

Seewald-Heeg, U.

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Editor

Mandl, T. u. C. Womser-Hacker

Footnote

Rez. in: Information - Wissenschaft und Praxis 57(2006) H.5, S.290-291 (C. Schindler): "Weniger als ein Jahr nach dem "Vierten Hildesheimer Evaluierungs- und Retrievalworkshop" (HIER 2005) im Juli 2005 ist der dazugehörige Tagungsband erschienen. Eingeladen hatte die Hildesheimer Informationswissenschaft um ihre Forschungsergebnisse und die einiger externer Experten zum Thema Information Retrieval einem Fachpublikum zu präsentieren und zur Diskussion zu stellen. Unter dem Titel "Effektive Information Retrieval Verfahren in Theorie und Praxis" sind nahezu sämtliche Beiträge des Workshops in dem nun erschienenen, 15 Beiträge umfassenden Band gesammelt. Mit dem Schwerpunkt Information Retrieval (IR) wird ein Teilgebiet der Informationswissenschaft vorgestellt, das schon immer im Zentrum informationswissenschaftlicher Forschung steht. Ob durch den Leistungsanstieg von Prozessoren und Speichermedien, durch die Verbreitung des Internet über nationale Grenzen hinweg oder durch den stetigen Anstieg der Wissensproduktion, festzuhalten ist, dass in einer zunehmend wechselseitig vernetzten Welt die Orientierung und das Auffinden von Dokumenten in großen Wissensbeständen zu einer zentralen Herausforderung geworden sind. Aktuelle Verfahrensweisen zu diesem Thema, dem Information Retrieval, präsentiert der neue Band anhand von praxisbezogenen Projekten und theoretischen Diskussionen. Das Kernthema Information Retrieval wird in dem Sammelband in die Bereiche Retrieval-Systeme, Digitale Bibliothek, Evaluierung und Multilinguale Systeme untergliedert. Die Artikel der einzelnen Sektionen sind insgesamt recht heterogen und bieten daher keine Überschneidungen inhaltlicher Art. Jedoch ist eine vollkommene thematische Abdeckung der unterschiedlichen Bereiche ebenfalls nicht gegeben, was bei der Präsentation von Forschungsergebnissen eines Institutes und seiner Kooperationspartner auch nur bedingt erwartet werden kann. So lässt sich sowohl in der Gliederung als auch in den einzelnen Beiträgen eine thematische Verdichtung erkennen, die das spezielle Profil und die Besonderheit der Hildesheimer Informationswissenschaft im Feld des Information Retrieval wiedergibt. Teil davon ist die mehrsprachige und interdisziplinäre Ausrichtung, die die Schnittstellen zwischen Informationswissenschaft, Sprachwissenschaft und Informatik in ihrer praxisbezogenen und internationalen Forschung fokussiert.