Search (86 results, page 1 of 5)

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Abstract

Canadian library records, bilingual by statute, are created according to a common set of rules and standards. Subject access to the catalogue remains language dependent. Even searches by classification in some OPACs rely first on an alphabetical index as an entering key. Fully bilingual OPACs with authority control and reciprocal references in one file have yet to appear. Thus far the Canadian Workplace Automation Research Center has produced ISIR/SIRI with an online bilingual thesaurus. The National Library of Canada has developed withh DOBIS a bilingual system providing automatic linkages between records and authority files. But true bilingual searching (a search in one language retrieving records in both languages) could be achieved by a built-in automatic translation module. Total accommodation of diacritical marks by terminal keyboards and display monitors is also a challenge to be met.

Source

Cataloging and classification quarterly. 10(1989) nos.1/2, S.141-163

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Abstract

The paper provides an illustration of the benefits of subject authority control improving multilingual subject access in NEBIS - Netzwerk von Bibliotheken und Informationsstellen in der Schweiz. This example of good practice focuses on some important aspects of classification and indexing. NEBIS subject authorities comprise a classification scheme and multilingual subject descriptor system. A bibliographic system supported by subject authority control empowers libraries as it enables them to expand and adjust vocabulary and link subjects to suit their specific audience. Most importantly it allows the management of different subject vocabularies in numerous languages. In addition, such an enriched subject index creates re-usable and shareable source of subject statements that has value in the wider context of information exchange. The illustrations and supporting arguments are based on indexing practice, subject authority control and use of classification in ETH-Bibliothek, which is the largest library within the NEBIS network.

Source

Classification and authority control: expanding resource discovery: proceedings of the International UDC Seminar 2015, 29-30 October 2015, Lisbon, Portugal. Eds.: Slavic, A. u. M.I. Cordeiro

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Abstract

This paper reports on the second part of an initiative of the authors on researching classification systems with the conceptual model defined by the Functional Requirements for Subject Authority Data (FRSAD) final report. In an earlier study, the authors explored whether the FRSAD conceptual model could be extended beyond subject authority data to model classification data. The focus of the current study is to determine if classification data modeled using FRSAD can be used to solve real-world discovery problems in multicultural and multilingual contexts. The paper discusses the relationships between entities (same type or different types) in the context of classification systems that involve multiple translations and /or multicultural implementations. Results of two case studies are presented in detail: (a) two instances of the DDC (DDC 22 in English, and the Swedish-English mixed translation of DDC 22), and (b) Chinese Library Classification. The use cases of conceptual models in practice are also discussed.

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Abstract

This article reports on the second part of an initiative of the authors on researching classification systems with the conceptual model defined by the Functional Requirements for Subject Authority Data (FRSAD) final report. In an earlier study, the authors explored whether the FRSAD conceptual model could be extended beyond subject authority data to model classification data. The focus of the current study is to determine if classification data modeled using FRSAD can be used to solve real-world discovery problems in multicultural and multilingual contexts. The article discusses the relationships between entities (same type or different types) in the context of classification systems that involve multiple translations and/or multicultural implementations. Results of two case studies are presented in detail: (a) two instances of the Dewey Decimal Classification [DDC] (DDC 22 in English, and the Swedish-English mixed translation of DDC 22), and (b) Chinese Library Classification. The use cases of conceptual models in practice are also discussed.

Source

Cataloging and classification quarterly. 52(2014) no.1, S.90-101

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Abstract

The present paper is offered as the first of a series of articles in which PRECIS will be reviewed as a potential multi-lingual system, having in mind the obvious need, notably in a European context, for standard and language independent methods of subject analysis and document description. This first paper outlines the origins of PRECIS, and considers its use in English language indexing. A second paper will deal in general terms with the syntactical model which is used for producing PRECIS input strings and index entries. Later papers will then review the application of this model to indexing in, firstly, the Germanic languages (e.g. German and Danish), and, secondly, the Romance languages, illustrated by French.

Theme

Preserved Context Index System (PRECIS)

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Abstract

In order to enhance the use of Universal Decimal Classification (UDC) numbers in information retrieval, the authors have represented classification with multilingual thesaurus descriptors and implemented this solution in an automated way. The authors illustrate a solution implemented in a BiblioPhil library system. The standard formats used are UNIMARC for subject authority records (i.e. the UDC-based multilingual thesaurus) and MARC XML support for data transfer. The multilingual thesaurus was built according to existing standards, the constituent parts of the classification notations being used as the basis for search terms in the multilingual information retrieval. The verbal equivalents, descriptors and non-descriptors, are used to expand the number of concepts and are given in Romanian, English and French. This approach saves the time of the indexer and provides more user-friendly and easier access to the bibliographic information. The multilingual aspect of the thesaurus enhances information access for a greater number of online users

Date

22. 7.2010 20:40:56

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Abstract

Many operational IR indexes are non-normalized, i.e. no lemmatization or stemming techniques, etc. have been employed in indexing. This poses a challenge for dictionary-based cross-language retrieval (CLIR), because translations are mostly lemmas. In this study, we face the challenge of dictionary-based CLIR in a non-normalized index. We test two optional approaches: FCG (Frequent Case Generation) and s-gramming. The idea of FCG is to automatically generate the most frequent inflected forms for a given lemma. FCG has been tested in monolingual retrieval and has been shown to be a good method for inflected retrieval, especially for highly inflected languages. S-gramming is an approximate string matching technique (an extension of n-gramming). The language pairs in our tests were English-Finnish, English-Swedish, Swedish-Finnish and Finnish-Swedish. Both our approaches performed quite well, but the results varied depending on the language pair. S-gramming and FCG performed quite equally in all the other language pairs except Finnish-Swedish, where s-gramming outperformed FCG.

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Abstract

A lot of information that is already available on the Web, or retrieved from local information systems and social networks is structured in data silos that are not semantically related. Semantic technologies make it emerge that the use of typed links that directly express their relations are an advantage for every application that can reuse the incorporated knowledge about the data. For this reason, data integration, through reengineering (e.g. triplify), or querying (e.g. D2R) is an important task in order to make information available for everyone. Thus, in order to build a semantic map of the data, we need knowledge about data items itself and the relation between heterogeneous data items. In this paper, we present our work of providing Lexical Linked Data (LLD) through a meta-model that contains all the resources and gives the possibility to retrieve and navigate them from different perspectives. We combine the existing work done on knowledge domains (based on the Information Coding Classification) within the Multilingual Lexical Linked Data Cloud (based on the RDF/OWL EurowordNet and the related integrated lexical resources (MultiWordNet, EuroWordNet, MEMODATA Lexicon, Hamburg Methaphor DB).

Date

22. 9.2014 19:01:18

Source

Knowledge organization in the 21st century: between historical patterns and future prospects. Proceedings of the Thirteenth International ISKO Conference 19-22 May 2014, Kraków, Poland. Ed.: Wieslaw Babik

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Abstract

For historical and cultural reasons, English phrases, especially proper nouns and new words, frequently appear in Web pages written primarily in East Asian languages such as Chinese, Korean, and Japanese. Although such English terms and their equivalences in these East Asian languages refer to the same concept, they are often erroneously treated as independent index units in traditional Information Retrieval (IR). This paper describes the degree to which the problem arises in IR and proposes a novel technique to solve it. Our method first extracts English terms from native Web documents in an East Asian language, and then unifies the extracted terms and their equivalences in the native language as one index unit. For Cross-Language Information Retrieval (CLIR), one of the major hindrances to achieving retrieval performance at the level of Mono-Lingual Information Retrieval (MLIR) is the translation of terms in search queries which can not be found in a bilingual dictionary. The Web mining approach proposed in this paper for concept unification of terms in different languages can also be applied to solve this well-known challenge in CLIR. Experimental results based on NTCIR and KT-Set test collections show that the high translation precision of our approach greatly improves performance of both Mono-Lingual and Cross-Language Information Retrieval.

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Date

27. 5.2001 16:22:10

Series

Cataloging and classification quarterly; vol.29, nos.1/2

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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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Abstract

Sehr viele Informationen sind bereits im Web verfügbar oder können aus isolierten strukturierten Datenspeichern wie Informationssystemen und sozialen Netzwerken gewonnen werden. Datenintegration durch Nachbearbeitung oder durch Suchmechanismen (z. B. D2R) ist deshalb wichtig, um Informationen allgemein verwendbar zu machen. Semantische Technologien ermöglichen die Verwendung definierter Verbindungen (typisierter Links), durch die ihre Beziehungen zueinander festgehalten werden, was Vorteile für jede Anwendung bietet, die das in Daten enthaltene Wissen wieder verwenden kann. Um ­eine semantische Daten-Landkarte herzustellen, benötigen wir Wissen über die einzelnen Daten und ihre Beziehung zu anderen Daten. Dieser Beitrag stellt unsere Arbeit zur Benutzung von Lexical Linked Data (LLD) durch ein Meta-Modell vor, das alle Ressourcen enthält und zudem die Möglichkeit bietet sie unter unterschiedlichen Gesichtspunkten aufzufinden. Wir verbinden damit bestehende Arbeiten über Wissensgebiete (basierend auf der Information Coding Classification) mit der Multilingual Lexical Linked Data Cloud (basierend auf der RDF/OWL-Repräsentation von EuroWordNet und den ähnlichen integrierten lexikalischen Ressourcen MultiWordNet, MEMODATA und die Hamburg Metapher DB).

Date

22. 9.2014 19:00:13

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Theme

Preserved Context Index System (PRECIS)

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Abstract

In this paper, after an introduction about problems of multilingual information languages, the rules and recommendations of the Guidelines for the establishment and development of multilingual thesauri for non-equivalence and partial equivalence of terms in different languages are discussed. Artificial terms are not very useful in searching, because most users are not willing to use a thesaurus to find the right descriptor. On the other hand indexers need guidance on how to index and therefore need a thesaurus with all desirable and necessary relations. It is suggested that bibliographic online systems can take over some of the functions for the searcher from the thesaurus and that a few new relations could be helpful to an indexer

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Theme

Preserved Context Index System (PRECIS)

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Date

2. 8.2001 8:55:22

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Abstract

Out of vocabulary words, mostly proper nouns and technical terms, are one main source of performance degradation in Cross Language Information Retrieval (CLIR) systems. Those are words not found in the dictionary. Bilingual dictionaries in general do not cover most proper nouns, which are usually primary keys in the query. As they are spelling variants of each other in most languages, using an approximate string matching technique against the target database index is the common approach taken to find the target language correspondents of the original query key. N-gram technique proved to be the most effective among other string matching techniques. The issue arises when the languages dealt with have different alphabets. Transliteration is then applied based on phonetic similarities between the languages involved. In this study, both transliteration and the n-gram technique are combined to generate possible transliterations in an English-Arabic CLIR system. We refer to this technique as Transliteration N-Gram (TNG). We further enhance TNG by applying Part Of Speech disambiguation on the set of transliterations so that words with a similar spelling, but a different meaning, are excluded. Experimental results show that TNG gives promising results, and enhanced TNG further improves performance.

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Theme

Preserved Context Index System (PRECIS)

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Source

Vortrag, IFLA Classification Section Workshop, Amsterdam, 20.8.1998