Search (45 results, page 2 of 3)

0.0030970925 = product of:
  0.009291277 = sum of:
    0.009291277 = weight(_text_:a in 7430) [ClassicSimilarity], result of:
      0.009291277 = score(doc=7430,freq=8.0), product of:
        0.05209492 = queryWeight, product of:
          1.153047 = idf(docFreq=37942, maxDocs=44218)
          0.045180224 = queryNorm
        0.17835285 = fieldWeight in 7430, product of:
          2.828427 = tf(freq=8.0), with freq of:
            8.0 = termFreq=8.0
          1.153047 = idf(docFreq=37942, maxDocs=44218)
          0.0546875 = fieldNorm(doc=7430)
  0.33333334 = coord(1/3)

Abstract

This article describes a framework for cross-language information retrieval that efficiently leverages statistical estimation of translation probabilities. The framework provides a unified perspective into which some earlier work on techniques for cross-language information retrieval based on translation probabilities can be cast. Modeling synonymy and filtering translation probabilities using bidirectional evidence are shown to yield a balance between retrieval effectiveness and query-time (or indexing-time) efficiency that seems well suited large-scale applications. Evaluations with six test collections show consistent improvements over strong baselines.

Type

a

0.0029348272 = product of:
  0.0088044815 = sum of:
    0.0088044815 = weight(_text_:a in 3946) [ClassicSimilarity], result of:
      0.0088044815 = score(doc=3946,freq=22.0), product of:
        0.05209492 = queryWeight, product of:
          1.153047 = idf(docFreq=37942, maxDocs=44218)
          0.045180224 = queryNorm
        0.16900843 = fieldWeight in 3946, product of:
          4.690416 = tf(freq=22.0), with freq of:
            22.0 = termFreq=22.0
          1.153047 = idf(docFreq=37942, maxDocs=44218)
          0.03125 = fieldNorm(doc=3946)
  0.33333334 = coord(1/3)

Abstract

Purpose - This paper seeks to examine image retrieval within two different 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. The study also aims to compare two different approaches for the indexing of ordinary images representing common objects: traditional image indexing with the use of a controlled vocabulary and free image indexing using uncontrolled vocabulary. Design/methodology/approach - This research uses three data collection methods. An analysis of the indexing terms was employed in order to examine the multiplicity of term types assigned to images. A simulation of the retrieval process involving a set of 30 images was performed with 60 participants. The quantification of the retrieval performance of each indexing approach was based on the usability measures, that is, effectiveness, efficiency and satisfaction of the user. Finally, a questionnaire was used to gather information on searcher satisfaction during and after the retrieval process. Findings - The results of this research are twofold. The analysis of indexing terms associated with all the 3,950 images provides a comprehensive description of the characteristics of the four non-combined indexing forms used for the study. Also, the retrieval simulation results offers information about the relative performance of the six indexing forms (combined and non-combined) in terms of their effectiveness, efficiency (temporal and human) and the image searcher's satisfaction. Originality/value - The findings of the study suggest that, in the near future, the information systems could benefit from allowing an increased coexistence of controlled vocabularies and uncontrolled vocabularies, resulting from collaborative image tagging, for example, and giving the users the possibility to dynamically participate in the image-indexing process, in a more user-centred way.

Type

a

0.0029264777 = product of:
  0.008779433 = sum of:
    0.008779433 = weight(_text_:a in 3956) [ClassicSimilarity], result of:
      0.008779433 = score(doc=3956,freq=14.0), product of:
        0.05209492 = queryWeight, product of:
          1.153047 = idf(docFreq=37942, maxDocs=44218)
          0.045180224 = queryNorm
        0.1685276 = fieldWeight in 3956, product of:
          3.7416575 = tf(freq=14.0), with freq of:
            14.0 = termFreq=14.0
          1.153047 = idf(docFreq=37942, maxDocs=44218)
          0.0390625 = fieldNorm(doc=3956)
  0.33333334 = coord(1/3)

Abstract

Purpose - This study aims to focus on the evaluation of systems for the automatic translation of questions destined to translingual question-answer (QA) systems. The efficacy of online translators when performing as tools in QA systems is analysed using a collection of documents in the Spanish language. Design/methodology/approach - Automatic translation is evaluated in terms of the functionality of actual translations produced by three online translators (Google Translator, Promt Translator, and Worldlingo) by means of objective and subjective evaluation measures, and the typology of errors produced was identified. For this purpose, a comparative study of the quality of the translation of factual questions of the CLEF collection of queries was carried out, from German and French to Spanish. Findings - It was observed that the rates of error for the three systems evaluated here are greater in the translations pertaining to the language pair German-Spanish . Promt was identified as the most reliable translator of the three (on average) for the two linguistic combinations evaluated. However, for the Spanish-German pair, a good assessment of the Google online translator was obtained as well. Most errors (46.38 percent) tended to be of a lexical nature, followed by those due to a poor translation of the interrogative particle of the query (31.16 percent). Originality/value - The evaluation methodology applied focuses above all on the finality of the translation. That is, does the resulting question serve as effective input into a translingual QA system? Thus, instead of searching for "perfection", the functionality of the question and its capacity to lead one to an adequate response are appraised. The results obtained contribute to the development of improved translingual QA systems.

Type

a

0.0029264777 = product of:
  0.008779433 = sum of:
    0.008779433 = weight(_text_:a in 3667) [ClassicSimilarity], result of:
      0.008779433 = score(doc=3667,freq=14.0), product of:
        0.05209492 = queryWeight, product of:
          1.153047 = idf(docFreq=37942, maxDocs=44218)
          0.045180224 = queryNorm
        0.1685276 = fieldWeight in 3667, product of:
          3.7416575 = tf(freq=14.0), with freq of:
            14.0 = termFreq=14.0
          1.153047 = idf(docFreq=37942, maxDocs=44218)
          0.0390625 = fieldNorm(doc=3667)
  0.33333334 = coord(1/3)

Abstract

Descriptive metadata play a key role in finding relevant search results in large amounts of unstructured data. However, current scientific audiovisual media are provided with little metadata, which makes them hard to find, let alone individual sequences. In this paper, the TIB / AV-Portal is presented as a use case where methods concerning the automatic generation of metadata, a semantic search and cross-lingual retrieval (German/English) have already been applied. These methods result in a better discoverability of the scientific audiovisual media hosted in the portal. Text, speech, and image content of the video are automatically indexed by specialised GND (Gemeinsame Normdatei) subject headings. A semantic search is established based on properties of the GND ontology. The cross-lingual retrieval uses English 'translations' that were derived by an ontology mapping (DBpedia i. a.). Further ways of increasing the discoverability and reuse of the metadata are publishing them as Linked Open Data and interlinking them with other data sets.

Type

a

0.0027093915 = product of:
  0.008128175 = sum of:
    0.008128175 = weight(_text_:a in 3707) [ClassicSimilarity], result of:
      0.008128175 = score(doc=3707,freq=12.0), product of:
        0.05209492 = queryWeight, product of:
          1.153047 = idf(docFreq=37942, maxDocs=44218)
          0.045180224 = queryNorm
        0.15602624 = fieldWeight in 3707, product of:
          3.4641016 = tf(freq=12.0), with freq of:
            12.0 = termFreq=12.0
          1.153047 = idf(docFreq=37942, maxDocs=44218)
          0.0390625 = fieldNorm(doc=3707)
  0.33333334 = coord(1/3)

Abstract

Purpose The purpose of this paper is threefold: to focus on the process of multilingual concept scheme construction and the challenges involved; to addresses concrete challenges faced in the construction process and especially those related to equivalence between terms and concepts; and to briefly outlines the translation strategies developed during the process of concept scheme construction. Design/methodology/approach The analysis is based on experience acquired during the establishment of the Finnish thesaurus and ontology service Finto as well as the trilingual General Finnish Ontology YSO, both of which are being maintained and further developed at the National Library of Finland. Findings Although uniform resource identifiers can be considered language-independent, they do not render concept schemes and their construction free of language-related challenges. The fundamental issue with all the challenges faced is how to maintain consistency and predictability when the nature of language requires each concept to be treated individually. The key to such challenges is to recognise the function of the vocabulary and the needs of its intended users. Social implications Open science increases the transparency of not only research products, but also metadata tools. Gaining a deeper understanding of the challenges involved in their construction is important for a great variety of users - e.g. indexers, vocabulary builders and information seekers. Today, multilingualism is an essential aspect at both the national and international information society level. Originality/value This paper draws on the practical challenges faced in concept scheme construction in a trilingual environment, with a focus on "concept scheme" as a translation and mapping unit.

Type

a

0.002654651 = product of:
  0.007963953 = sum of:
    0.007963953 = weight(_text_:a in 2974) [ClassicSimilarity], result of:
      0.007963953 = score(doc=2974,freq=8.0), product of:
        0.05209492 = queryWeight, product of:
          1.153047 = idf(docFreq=37942, maxDocs=44218)
          0.045180224 = queryNorm
        0.15287387 = fieldWeight in 2974, product of:
          2.828427 = tf(freq=8.0), with freq of:
            8.0 = termFreq=8.0
          1.153047 = idf(docFreq=37942, maxDocs=44218)
          0.046875 = fieldNorm(doc=2974)
  0.33333334 = coord(1/3)

Abstract

General graph random walk has been successfully applied in multi-document summarization, but it has some limitations to process documents by this way. In this paper, we propose a novel hypergraph based vertex-reinforced random walk framework for multi-document summarization. The framework first exploits the Hierarchical Dirichlet Process (HDP) topic model to learn a word-topic probability distribution in sentences. Then the hypergraph is used to capture both cluster relationship based on the word-topic probability distribution and pairwise similarity among sentences. Finally, a time-variant random walk algorithm for hypergraphs is developed to rank sentences which ensures sentence diversity by vertex-reinforcement in summaries. Experimental results on the public available dataset demonstrate the effectiveness of our framework.

Type

a

0.002654651 = product of:
  0.007963953 = sum of:
    0.007963953 = weight(_text_:a in 3187) [ClassicSimilarity], result of:
      0.007963953 = score(doc=3187,freq=8.0), product of:
        0.05209492 = queryWeight, product of:
          1.153047 = idf(docFreq=37942, maxDocs=44218)
          0.045180224 = queryNorm
        0.15287387 = fieldWeight in 3187, product of:
          2.828427 = tf(freq=8.0), with freq of:
            8.0 = termFreq=8.0
          1.153047 = idf(docFreq=37942, maxDocs=44218)
          0.046875 = fieldNorm(doc=3187)
  0.33333334 = coord(1/3)

Abstract

The quality of stemming algorithms is typically measured in two different ways: (i) how accurately they map the variant forms of a word to the same stem; or (ii) how much improvement they bring to Information Retrieval systems. In this article, we evaluate various stemming algorithms, in four languages, in terms of accuracy and in terms of their aid to Information Retrieval. The aim is to assess whether the most accurate stemmers are also the ones that bring the biggest gain in Information Retrieval. Experiments in English, French, Portuguese, and Spanish show that this is not always the case, as stemmers with higher error rates yield better retrieval quality. As a byproduct, we also identified the most accurate stemmers and the best for Information Retrieval purposes.

Type

a

0.002212209 = product of:
  0.0066366266 = sum of:
    0.0066366266 = weight(_text_:a in 3278) [ClassicSimilarity], result of:
      0.0066366266 = score(doc=3278,freq=2.0), product of:
        0.05209492 = queryWeight, product of:
          1.153047 = idf(docFreq=37942, maxDocs=44218)
          0.045180224 = queryNorm
        0.12739488 = fieldWeight in 3278, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          1.153047 = idf(docFreq=37942, maxDocs=44218)
          0.078125 = fieldNorm(doc=3278)
  0.33333334 = coord(1/3)

Type

a

0.002212209 = product of:
  0.0066366266 = sum of:
    0.0066366266 = weight(_text_:a in 4244) [ClassicSimilarity], result of:
      0.0066366266 = score(doc=4244,freq=8.0), product of:
        0.05209492 = queryWeight, product of:
          1.153047 = idf(docFreq=37942, maxDocs=44218)
          0.045180224 = queryNorm
        0.12739488 = fieldWeight in 4244, product of:
          2.828427 = tf(freq=8.0), with freq of:
            8.0 = termFreq=8.0
          1.153047 = idf(docFreq=37942, maxDocs=44218)
          0.0390625 = fieldNorm(doc=4244)
  0.33333334 = coord(1/3)

Abstract

As an effective technique for improving retrieval effectiveness, relevance feedback (RF) has been widely studied in both monolingual and translingual information retrieval (TLIR). The studies of RF in TLIR have been focused on query expansion (QE), in which queries are reformulated before and/or after they are translated. However, RF in TLIR actually not only can help select better query terms, but also can enhance query translation by adjusting translation probabilities and even resolving some out-of-vocabulary terms. In this paper, we propose a novel relevance feedback method called translation enhancement (TE), which uses the extracted translation relationships from relevant documents to revise the translation probabilities of query terms and to identify extra available translation alternatives so that the translated queries are more tuned to the current search. We studied TE using pseudo-relevance feedback (PRF) and interactive relevance feedback (IRF). Our results show that TE can significantly improve TLIR with both types of relevance feedback methods, and that the improvement is comparable to that of query expansion. More importantly, the effects of translation enhancement and query expansion are complementary. Their integration can produce further improvement, and makes TLIR more robust for a variety of queries.

Type

a

0.002212209 = product of:
  0.0066366266 = sum of:
    0.0066366266 = weight(_text_:a in 2295) [ClassicSimilarity], result of:
      0.0066366266 = score(doc=2295,freq=8.0), product of:
        0.05209492 = queryWeight, product of:
          1.153047 = idf(docFreq=37942, maxDocs=44218)
          0.045180224 = queryNorm
        0.12739488 = fieldWeight in 2295, product of:
          2.828427 = tf(freq=8.0), with freq of:
            8.0 = termFreq=8.0
          1.153047 = idf(docFreq=37942, maxDocs=44218)
          0.0390625 = fieldNorm(doc=2295)
  0.33333334 = coord(1/3)

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

Type

a

0.00197866 = product of:
  0.00593598 = sum of:
    0.00593598 = weight(_text_:a in 4800) [ClassicSimilarity], result of:
      0.00593598 = score(doc=4800,freq=10.0), product of:
        0.05209492 = queryWeight, product of:
          1.153047 = idf(docFreq=37942, maxDocs=44218)
          0.045180224 = queryNorm
        0.11394546 = fieldWeight in 4800, product of:
          3.1622777 = tf(freq=10.0), with freq of:
            10.0 = termFreq=10.0
          1.153047 = idf(docFreq=37942, maxDocs=44218)
          0.03125 = fieldNorm(doc=4800)
  0.33333334 = coord(1/3)

Abstract

The usefulness of online geological maps is hindered by linguistic barriers. Multilingual geoscience thesauri alleviate linguistic barriers of geological maps. However, the benefits of multilingual geoscience thesauri for online geological maps are less studied. In this regard, we developed a multilingual thesaurus of geological time scale (GTS) to alleviate linguistic barriers of GTS records among online geological maps. We extended the Simple Knowledge Organization System (SKOS) model to represent the ordinal hierarchical structure of GTS terms. We collected GTS terms in seven languages and encoded them into a thesaurus by using the extended SKOS model. We implemented methods of characteristic-oriented term retrieval in JavaScript programs for accessing Web Map Services (WMS), recognizing GTS terms, and making translations. With the developed thesaurus and programs, we set up a pilot system to test recognitions and translations of GTS terms in online geological maps. Results of this pilot system proved the accuracy of the developed thesaurus and the functionality of the developed programs. Therefore, with proper deployments, SKOS-based multilingual geoscience thesauri can be functional for alleviating linguistic barriers among online geological maps and, thus, improving their interoperability.

Type

a

0.00197866 = product of:
  0.00593598 = sum of:
    0.00593598 = weight(_text_:a in 1832) [ClassicSimilarity], result of:
      0.00593598 = score(doc=1832,freq=10.0), product of:
        0.05209492 = queryWeight, product of:
          1.153047 = idf(docFreq=37942, maxDocs=44218)
          0.045180224 = queryNorm
        0.11394546 = fieldWeight in 1832, product of:
          3.1622777 = tf(freq=10.0), with freq of:
            10.0 = termFreq=10.0
          1.153047 = idf(docFreq=37942, maxDocs=44218)
          0.03125 = fieldNorm(doc=1832)
  0.33333334 = coord(1/3)

Abstract

Welcome to the very first issue of EuropeanaTech Insight, a multimedia publication about research and development within the EuropeanaTech community. EuropeanaTech is a very active community. It spans all of Europe and is made up of technical experts from the various disciplines within digital cultural heritage. At any given moment, members can be found presenting their work in project meetings, seminars and conferences around the world. Now, through EuropeanaTech Insight, we can share that inspiring work with the whole community. In our first three issues, we're showcasing topics discussed at the EuropeanaTech 2015 Conference, an exciting event that gave rise to lots of innovative ideas and fruitful conversations on the themes of data quality, data modelling, open data, data re-use, multilingualism and discovery. Welcome, bienvenue, bienvenido, Välkommen, Tervetuloa to the first Issue of EuropeanaTech Insight. Are we talking your language? No? Well I can guarantee you Europeana is. One of the European Union's great beauties and strengths is its diversity. That diversity is perhaps most evident in the 24 different languages spoken in the EU. Making it possible for all European citizens to easily and seamlessly communicate in their native language with others who do not speak that language is a huge technical undertaking. Translating documents, news, speeches and historical texts was once exclusively done manually. Clearly, that takes a huge amount of time and resources and means that not everything can be translated... However, with the advances in machine and automatic translation, it's becoming more possible to provide instant and pretty accurate translations. Europeana provides access to over 40 million digitised cultural heritage offering content in over 33 languages. But what value does Europeana provide if people can only find results in their native language? None. That's why the EuropeanaTech community is collectively working towards making it more possible for everyone to discover our collections in their native language. In this issue of EuropeanaTech Insight, we hear from community members who are making great strides in machine translation and enrichment tools to help improve not only access to data, but also how we retrieve, browse and understand it.

Content

Juliane Stiller, J.: Automatic Solutions to Improve Multilingual Access in Europeana / Vila-Suero, D. and A. Gómez-Pérez: Multilingual Linked Data / Pilos, S.: Automated Translation: Connecting Culture / Karlgren, J.: Big Data, Libraries, and Multilingual New Text / Ziedins, J.: Latvia translates with hugo.lv

0.0018771215 = product of:
  0.0056313644 = sum of:
    0.0056313644 = weight(_text_:a in 2782) [ClassicSimilarity], result of:
      0.0056313644 = score(doc=2782,freq=4.0), product of:
        0.05209492 = queryWeight, product of:
          1.153047 = idf(docFreq=37942, maxDocs=44218)
          0.045180224 = queryNorm
        0.10809815 = fieldWeight in 2782, product of:
          2.0 = tf(freq=4.0), with freq of:
            4.0 = termFreq=4.0
          1.153047 = idf(docFreq=37942, maxDocs=44218)
          0.046875 = fieldNorm(doc=2782)
  0.33333334 = coord(1/3)

Type

a

0.0018771215 = product of:
  0.0056313644 = sum of:
    0.0056313644 = weight(_text_:a in 3034) [ClassicSimilarity], result of:
      0.0056313644 = score(doc=3034,freq=4.0), product of:
        0.05209492 = queryWeight, product of:
          1.153047 = idf(docFreq=37942, maxDocs=44218)
          0.045180224 = queryNorm
        0.10809815 = fieldWeight in 3034, product of:
          2.0 = tf(freq=4.0), with freq of:
            4.0 = termFreq=4.0
          1.153047 = idf(docFreq=37942, maxDocs=44218)
          0.046875 = fieldNorm(doc=3034)
  0.33333334 = coord(1/3)

Abstract

This paper reports on an ongoing investigation of mixed translation models for the Dewey Decimal Classification (DDC) system to support classification and access. A mixed translation uses DDC classes in the vernacular to form the basic framework of the mixed edition; English-language records are ingested directly to complete hierarchies where needed. Separate indexes of available terminology in the vernacular and English are provided. Specific Norwegian and Swedish mixed models are described, along with testing results of the Norwegian model. General implications of mixed translation models for knowledge organization in multilingual environments are considered.

Type

a

0.0018771215 = product of:
  0.0056313644 = sum of:
    0.0056313644 = weight(_text_:a in 2203) [ClassicSimilarity], result of:
      0.0056313644 = score(doc=2203,freq=4.0), product of:
        0.05209492 = queryWeight, product of:
          1.153047 = idf(docFreq=37942, maxDocs=44218)
          0.045180224 = queryNorm
        0.10809815 = fieldWeight in 2203, product of:
          2.0 = tf(freq=4.0), with freq of:
            4.0 = termFreq=4.0
          1.153047 = idf(docFreq=37942, maxDocs=44218)
          0.046875 = fieldNorm(doc=2203)
  0.33333334 = coord(1/3)

Abstract

This paper gives an overview of the history, development, and structure of the electronic thesauri produced and maintained by the Getty Research Institute (GRI). We describe the evolution of the Art & Architecture Thesaurus (AAT®), the Getty Thesaurus of Geographic Names (TGN®), and the Union List of Artist Names (ULAN®) as multilingual, cross-cultural knowledge organization systems (KOS); the factors that make them unique; and their potential, when expressed as Linked Open Data (LOD) to play a key role in the Semantic Web.

Type

a

0.0017697671 = product of:
  0.0053093014 = sum of:
    0.0053093014 = weight(_text_:a in 361) [ClassicSimilarity], result of:
      0.0053093014 = score(doc=361,freq=8.0), product of:
        0.05209492 = queryWeight, product of:
          1.153047 = idf(docFreq=37942, maxDocs=44218)
          0.045180224 = queryNorm
        0.10191591 = fieldWeight in 361, product of:
          2.828427 = tf(freq=8.0), with freq of:
            8.0 = termFreq=8.0
          1.153047 = idf(docFreq=37942, maxDocs=44218)
          0.03125 = fieldNorm(doc=361)
  0.33333334 = coord(1/3)

Abstract

We are living in a multilingual world and the diversity in languages which are used to interact with information access systems has generated a wide variety of challenges to be addressed by computer and information scientists. The growing amount of non-English information accessible globally and the increased worldwide exposure of enterprises also necessitates the adaptation of Information Retrieval (IR) methods to new, multilingual settings.Peters, Braschler and Clough present a comprehensive description of the technologies involved in designing and developing systems for Multilingual Information Retrieval (MLIR). They provide readers with broad coverage of the various issues involved in creating systems to make accessible digitally stored materials regardless of the language(s) they are written in. Details on Cross-Language Information Retrieval (CLIR) are also covered that help readers to understand how to develop retrieval systems that cross language boundaries. Their work is divided into six chapters and accompanies the reader step-by-step through the various stages involved in building, using and evaluating MLIR systems. The book concludes with some examples of recent applications that utilise MLIR technologies. Some of the techniques described have recently started to appear in commercial search systems, while others have the potential to be part of future incarnations.The book is intended for graduate students, scholars, and practitioners with a basic understanding of classical text retrieval methods. It offers guidelines and information on all aspects that need to be taken into consideration when building MLIR systems, while avoiding too many 'hands-on details' that could rapidly become obsolete. Thus it bridges the gap between the material covered by most of the classical IR textbooks and the novel requirements related to the acquisition and dissemination of information in whatever language it is stored.

0.0017697671 = product of:
  0.0053093014 = sum of:
    0.0053093014 = weight(_text_:a in 3558) [ClassicSimilarity], result of:
      0.0053093014 = score(doc=3558,freq=2.0), product of:
        0.05209492 = queryWeight, product of:
          1.153047 = idf(docFreq=37942, maxDocs=44218)
          0.045180224 = queryNorm
        0.10191591 = fieldWeight in 3558, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          1.153047 = idf(docFreq=37942, maxDocs=44218)
          0.0625 = fieldNorm(doc=3558)
  0.33333334 = coord(1/3)

Type

a

0.001564268 = product of:
  0.004692804 = sum of:
    0.004692804 = weight(_text_:a in 3881) [ClassicSimilarity], result of:
      0.004692804 = score(doc=3881,freq=4.0), product of:
        0.05209492 = queryWeight, product of:
          1.153047 = idf(docFreq=37942, maxDocs=44218)
          0.045180224 = queryNorm
        0.090081796 = fieldWeight in 3881, product of:
          2.0 = tf(freq=4.0), with freq of:
            4.0 = termFreq=4.0
          1.153047 = idf(docFreq=37942, maxDocs=44218)
          0.0390625 = fieldNorm(doc=3881)
  0.33333334 = coord(1/3)

Abstract

Der Bibliotheksverbund NEBIS (Netzwerk von Bibliotheken und Informationsstellen in der Schweiz) ist der grösste Verbund wissenschaftlicher Bibliotheken der Schweiz. Ihm gehören rund 140 Bibliotheken an 154 Standorten aus allen Landesteilen der Schweiz an. Im NEBIS arbeiten Bibliotheken sowohl aus der Deutschschweiz als auch aus den Französisch und Italienisch sprechenden Landesteilen. Der Anteil der nicht-deutschsprachigen Bibliotheken beträgt im NEBIS über 15 Prozent. Auf den Jahresbeginn 2016 hat der NEBIS-Verbund das bisher verwendete Regelwerk KIDS (Katalogisierungsregeln des IDS) durch das internationale Regelwerk RDA sowie die hauseigene Normdatenbank durch die deutschorientierte Normdatenbank GND abgelöst. Der Zustand der französischsprachigen Übersetzung der RDA sowie die Übersetzung der Anwendungsregeln des D-A-CH Raumes waren eine der grössten Herausforderungen bei der Einführung im Verbund. In einer mehrsprachigen Umgebung mit einer monolingualen Datenbank wie der GND zu arbeiten, bedeutete besonders für die französischsprachigen Bibliotheken viel Umstellung und Flexibilität. Die Arbeit mit deutschen Begriffen wie zum Beispiel die Berufsbegriffe in der GND erfordert sowohl von der NEBIS-Verbundzentrale wie auch von den französischsprachigen Bibliotheken einen ausserordentlichen Effort. Der NEBIS-Verbund wird auch künftig darauf angewiesen sein, dass die französische Übersetzung der RDA sowie die Übersetzung der Anwendungsregeln möglichst aktuell bleibt. Zudem wird auch im Bereich GND weiterhin eine flexible und geduldige Arbeitsweise aller Beteiligten erforderlich sein.

Type

a

0.0015485462 = product of:
  0.0046456386 = sum of:
    0.0046456386 = weight(_text_:a in 4506) [ClassicSimilarity], result of:
      0.0046456386 = score(doc=4506,freq=2.0), product of:
        0.05209492 = queryWeight, product of:
          1.153047 = idf(docFreq=37942, maxDocs=44218)
          0.045180224 = queryNorm
        0.089176424 = fieldWeight in 4506, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          1.153047 = idf(docFreq=37942, maxDocs=44218)
          0.0546875 = fieldNorm(doc=4506)
  0.33333334 = coord(1/3)

Type

a

0.0015485462 = product of:
  0.0046456386 = sum of:
    0.0046456386 = weight(_text_:a in 902) [ClassicSimilarity], result of:
      0.0046456386 = score(doc=902,freq=2.0), product of:
        0.05209492 = queryWeight, product of:
          1.153047 = idf(docFreq=37942, maxDocs=44218)
          0.045180224 = queryNorm
        0.089176424 = fieldWeight in 902, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          1.153047 = idf(docFreq=37942, maxDocs=44218)
          0.0546875 = fieldNorm(doc=902)
  0.33333334 = coord(1/3)

Type

a