Search (10 results, page 1 of 1)

0.0039349417 = product of:
  0.015739767 = sum of:
    0.015739767 = weight(_text_:information in 1261) [ClassicSimilarity], result of:
      0.015739767 = score(doc=1261,freq=14.0), product of:
        0.06134496 = queryWeight, product of:
          1.7554779 = idf(docFreq=20772, maxDocs=44218)
          0.034944877 = queryNorm
        0.256578 = fieldWeight in 1261, product of:
          3.7416575 = tf(freq=14.0), with freq of:
            14.0 = termFreq=14.0
          1.7554779 = idf(docFreq=20772, maxDocs=44218)
          0.0390625 = fieldNorm(doc=1261)
  0.25 = coord(1/4)

Abstract

We are rapidly constructing an extensive network infrastructure for moving information across national boundaries, but much remains to be done before linguistic barriers can be surmounted as effectively as geographic ones. Users seeking information from a digital library could benefit from the ability to query large collections once using a single language, even when more than one language is present in the collection. If the information they locate is not available in a language that they can read, some form of translation will be needed. At present, multilingual thesauri such as EUROVOC help to address this challenge by facilitating controlled vocabulary search using terms from several languages, and services such as INSPEC produce English abstracts for documents in other languages. On the other hand, support for free text searching across languages is not yet widely deployed, and fully automatic machine translation is presently neither sufficiently fast nor sufficiently accurate to adequately support interactive cross-language information seeking. An active and rapidly growing research community has coalesced around these and other related issues, applying techniques drawn from several fields - notably information retrieval and natural language processing - to provide access to large multilingual collections.

Theme

Information Gateway

0.0035694435 = product of:
  0.014277774 = sum of:
    0.014277774 = weight(_text_:information in 6068) [ClassicSimilarity], result of:
      0.014277774 = score(doc=6068,freq=18.0), product of:
        0.06134496 = queryWeight, product of:
          1.7554779 = idf(docFreq=20772, maxDocs=44218)
          0.034944877 = queryNorm
        0.23274568 = fieldWeight in 6068, product of:
          4.2426405 = tf(freq=18.0), with freq of:
            18.0 = termFreq=18.0
          1.7554779 = idf(docFreq=20772, maxDocs=44218)
          0.03125 = fieldNorm(doc=6068)
  0.25 = coord(1/4)

Abstract

Over the past 50 years, a variety of language-related capabilities has been developed in machine translation, information retrieval, speech recognition, text summarization, and so on. These applications rest upon a set of core techniques such as language modeling, information extraction, parsing, generation, and multimedia planning and integration; and they involve methods using statistics, rules, grammars, lexicons, ontologies, training techniques, and so on. It is a puzzling fact that although all of this work deals with language in some form or other, the major applications have each developed a separate research field. For example, there is no reason why speech recognition techniques involving n-grams and hidden Markov models could not have been used in machine translation 15 years earlier than they were, or why some of the lexical and semantic insights from the subarea called Computational Linguistics are still not used in information retrieval.
This picture will rapidly change. The twin challenges of massive information overload via the web and ubiquitous computers present us with an unavoidable task: developing techniques to handle multilingual and multi-modal information robustly and efficiently, with as high quality performance as possible. The most effective way for us to address such a mammoth task, and to ensure that our various techniques and applications fit together, is to start talking across the artificial research boundaries. Extending the current technologies will require integrating the various capabilities into multi-functional and multi-lingual natural language systems. However, at this time there is no clear vision of how these technologies could or should be assembled into a coherent framework. What would be involved in connecting a speech recognition system to an information retrieval engine, and then using machine translation and summarization software to process the retrieved text? How can traditional parsing and generation be enhanced with statistical techniques? What would be the effect of carefully crafted lexicons on traditional information retrieval? At which points should machine translation be interleaved within information retrieval systems to enable multilingual processing?

0.0033653039 = product of:
  0.013461215 = sum of:
    0.013461215 = weight(_text_:information in 1233) [ClassicSimilarity], result of:
      0.013461215 = score(doc=1233,freq=4.0), product of:
        0.06134496 = queryWeight, product of:
          1.7554779 = idf(docFreq=20772, maxDocs=44218)
          0.034944877 = queryNorm
        0.21943474 = fieldWeight in 1233, product of:
          2.0 = tf(freq=4.0), with freq of:
            4.0 = termFreq=4.0
          1.7554779 = idf(docFreq=20772, maxDocs=44218)
          0.0625 = fieldNorm(doc=1233)
  0.25 = coord(1/4)

Abstract

With the recent rapid diffusion over the international computer networks of world-wide distributed document bases, the question of multilingual access and multilingual information retrieval is becoming increasingly relevant. We briefly discuss just some of the issues that must be addressed in order to implement a multilingual interface for a Digital Library system and describe our own approach to this problem.

Theme

Information Gateway

0.0033653039 = product of:
  0.013461215 = sum of:
    0.013461215 = weight(_text_:information in 1742) [ClassicSimilarity], result of:
      0.013461215 = score(doc=1742,freq=16.0), product of:
        0.06134496 = queryWeight, product of:
          1.7554779 = idf(docFreq=20772, maxDocs=44218)
          0.034944877 = queryNorm
        0.21943474 = fieldWeight in 1742, product of:
          4.0 = tf(freq=16.0), with freq of:
            16.0 = termFreq=16.0
          1.7554779 = idf(docFreq=20772, maxDocs=44218)
          0.03125 = fieldNorm(doc=1742)
  0.25 = coord(1/4)

Abstract

While being theoretically so widely available, information can be restricted from a more general use by linguistic barriers. The linguistic aspects of the information languages and particularly the chances of an enhanced access to information by means of multilingual access facilities will make the substance of this thesis. The main problem of this research is thus to demonstrate that information retrieval can be improved by using multilingual thesaurus terms based on an intermediate or switching language to search with. Universal classification systems in general can play the role of switching languages for reasons dealt with in the forthcoming pages. The Universal Decimal Classification (UDC) in particular is the classification system used as example of a switching language for our objectives. The question may arise: why a universal classification system and not another thesaurus? Because the UDC like most of the classification systems uses symbols. Therefore, it is language independent and the problems of compatibility between such a thesaurus and different other thesauri in different languages are avoided. Another question may still arise? Why not then, assign running numbers to the descriptors in a thesaurus and make a switching language out of the resulting enumerative system? Because of some other characteristics of the UDC: hierarchical structure and terminological richness, consistency and control. One big problem to find an answer to is: can a thesaurus be made having as a basis a classification system in any and all its parts? To what extent this question can be given an affirmative answer? This depends much on the attributes of the universal classification system which can be favourably used to this purpose. Examples of different situations will be given and discussed upon beginning with those classes of UDC which are best fitted for building a thesaurus structure out of them (classes which are both hierarchical and faceted)...

Content

Inhalt: INFORMATION LANGUAGES: A LINGUISTIC APPROACH MULTILINGUAL ASPECTS IN INFORMATION STORAGE AND RETRIEVAL COMPATIBILITY AND CONVERTIBILITY OF INFORMATION LANGUAGES CURRENT TRENDS IN MULTILINGUAL ACCESS BUILDING UDC-BASED MULTILINGUAL THESAURI ONLINE APPLICATIONS OF THE UDC-BASED MULTILINGUAL THESAURI THE IMPACT OF SPECIFICITY ON THE RETRIEVAL POWER OF A UDC-BASED MULTILINGUAL THESAURUS FINAL REMARKS AND GENERAL CONCLUSIONS Proefschrift voorgelegd tot het behalen van de graad van doctor in de Taal- en Letterkunde aan de Universiteit Antwerpen. - Vgl.: http://dlist.sir.arizona.edu/1862/.

0.0029745363 = product of:
  0.011898145 = sum of:
    0.011898145 = weight(_text_:information in 2342) [ClassicSimilarity], result of:
      0.011898145 = score(doc=2342,freq=2.0), product of:
        0.06134496 = queryWeight, product of:
          1.7554779 = idf(docFreq=20772, maxDocs=44218)
          0.034944877 = queryNorm
        0.19395474 = fieldWeight in 2342, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          1.7554779 = idf(docFreq=20772, maxDocs=44218)
          0.078125 = fieldNorm(doc=2342)
  0.25 = coord(1/4)

Source

Journal of digital information. 2(2002) no.2,

0.0029745363 = product of:
  0.011898145 = sum of:
    0.011898145 = weight(_text_:information in 1296) [ClassicSimilarity], result of:
      0.011898145 = score(doc=1296,freq=2.0), product of:
        0.06134496 = queryWeight, product of:
          1.7554779 = idf(docFreq=20772, maxDocs=44218)
          0.034944877 = queryNorm
        0.19395474 = fieldWeight in 1296, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          1.7554779 = idf(docFreq=20772, maxDocs=44218)
          0.078125 = fieldNorm(doc=1296)
  0.25 = coord(1/4)

0.002327943 = product of:
  0.009311772 = sum of:
    0.009311772 = weight(_text_:information in 1164) [ClassicSimilarity], result of:
      0.009311772 = score(doc=1164,freq=10.0), product of:
        0.06134496 = queryWeight, product of:
          1.7554779 = idf(docFreq=20772, maxDocs=44218)
          0.034944877 = queryNorm
        0.1517936 = fieldWeight in 1164, product of:
          3.1622777 = tf(freq=10.0), with freq of:
            10.0 = termFreq=10.0
          1.7554779 = idf(docFreq=20772, maxDocs=44218)
          0.02734375 = fieldNorm(doc=1164)
  0.25 = coord(1/4)

Abstract

The explosive growth of the Internet and other sources of networked information have made automatic mediation of access to networked information sources an increasingly important problem. Much of this information is expressed as electronic text, and it is becoming practical to automatically convert some printed documents and recorded speech to electronic text as well. Thus, automated systems capable of detecting useful documents are finding widespread application. With even a small number of languages it can be inconvenient to issue the same query repeatedly in every language, so users who are able to read more than one language will likely prefer a multilingual text retrieval system over a collection of monolingual systems. And since reading ability in a language does not always imply fluent writing ability in that language, such users will likely find cross-language text retrieval particularly useful for languages in which they are less confident of their ability to express their information needs effectively. The use of such systems can be also be beneficial if the user is able to read only a single language. For example, when only a small portion of the document collection will ever be examined by the user, performing retrieval before translation can be significantly more economical than performing translation before retrieval. So when the application is sufficiently important to justify the time and effort required for translation, those costs can be minimized if an effective cross-language text retrieval system is available. Even when translation is not available, there are circumstances in which cross-language text retrieval could be useful to a monolingual user. For example, a researcher might find a paper published in an unfamiliar language useful if that paper contains references to works by the same author that are in the researcher's native language.
Multilingual text retrieval can be defined as selection of useful documents from collections that may contain several languages (English, French, Chinese, etc.). This formulation allows for the possibility that individual documents might contain more than one language, a common occurrence in some applications. Both cross-language and within-language retrieval are included in this formulation, but it is the cross-language aspect of the problem which distinguishes multilingual text retrieval from its well studied monolingual counterpart. At the SIGIR 96 workshop on "Cross-Linguistic Information Retrieval" the participants discussed the proliferation of terminology being used to describe the field and settled on "Cross-Language" as the best single description of the salient aspect of the problem. "Multilingual" was felt to be too broad, since that term has also been used to describe systems able to perform within-language retrieval in more than one language but that lack any cross-language capability. "Cross-lingual" and "cross-linguistic" were felt to be equally good descriptions of the field, but "crosslanguage" was selected as the preferred term in the interest of standardization. Unfortunately, at about the same time the U.S. Defense Advanced Research Projects Agency (DARPA) introduced "translingual" as their preferred term, so we are still some distance from reaching consensus on this matter.

0.001803217 = product of:
  0.007212868 = sum of:
    0.007212868 = weight(_text_:information in 1263) [ClassicSimilarity], result of:
      0.007212868 = score(doc=1263,freq=6.0), product of:
        0.06134496 = queryWeight, product of:
          1.7554779 = idf(docFreq=20772, maxDocs=44218)
          0.034944877 = queryNorm
        0.11757882 = fieldWeight in 1263, product of:
          2.4494898 = tf(freq=6.0), with freq of:
            6.0 = termFreq=6.0
          1.7554779 = idf(docFreq=20772, maxDocs=44218)
          0.02734375 = fieldNorm(doc=1263)
  0.25 = coord(1/4)

Abstract

The Internet would not be very useful if communication were limited to textual exchanges between speakers of English located in the United States. Rather, its value lies in its ability to enable people from multiple nations, speaking multiple languages, to employ multiple media in interacting with each other. While computer networks broke through national boundaries long ago, they remain much more effective for textual communication than for exchanges of sound, images, or mixed media -- and more effective for communication in English than for exchanges in most other languages, much less interactions involving multiple languages. Supporting searching and display in multiple languages is an increasingly important issue for all digital libraries accessible on the Internet. Even if a digital library contains materials in only one language, the content needs to be searchable and displayable on computers in countries speaking other languages. We need to exchange data between digital libraries, whether in a single language or in multiple languages. Data exchanges may be large batch updates or interactive hyperlinks. In any of these cases, character sets must be represented in a consistent manner if exchanges are to succeed. Issues of interoperability, portability, and data exchange related to multi-lingual character sets have received surprisingly little attention in the digital library community or in discussions of standards for information infrastructure, except in Europe. The landmark collection of papers on Standards Policy for Information Infrastructure, for example, contains no discussion of multi-lingual issues except for a passing reference to the Unicode standard. The goal of this short essay is to draw attention to the multi-lingual issues involved in designing digital libraries accessible on the Internet. Many of the multi-lingual design issues parallel those of multi-media digital libraries, a topic more familiar to most readers of D-Lib Magazine. This essay draws examples from multi-media DLs to illustrate some of the urgent design challenges in creating a globally distributed network serving people who speak many languages other than English. First we introduce some general issues of medium, culture, and language, then discuss the design challenges in the transition from local to global systems, lastly addressing technical matters. The technical issues involve the choice of character sets to represent languages, similar to the choices made in representing images or sound. However, the scale of the language problem is far greater. Standards for multi-media representation are being adopted fairly rapidly, in parallel with the availability of multi-media content in electronic form. By contrast, we have hundreds (and sometimes thousands) of years worth of textual materials in hundreds of languages, created long before data encoding standards existed. Textual content from past and present is being encoded in language and application-specific representations that are difficult to exchange without losing data -- if they exchange at all. We illustrate the multi-language DL challenge with examples drawn from the research library community, which typically handles collections of materials in 400 or so languages. These are problems faced not only by developers of digital libraries, but by those who develop and manage any communication technology that crosses national or linguistic boundaries.

Theme

Information Gateway

0.0017847219 = product of:
  0.0071388874 = sum of:
    0.0071388874 = weight(_text_:information in 2625) [ClassicSimilarity], result of:
      0.0071388874 = score(doc=2625,freq=2.0), product of:
        0.06134496 = queryWeight, product of:
          1.7554779 = idf(docFreq=20772, maxDocs=44218)
          0.034944877 = queryNorm
        0.116372846 = fieldWeight in 2625, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          1.7554779 = idf(docFreq=20772, maxDocs=44218)
          0.046875 = fieldNorm(doc=2625)
  0.25 = coord(1/4)

Content

Beitrag während: World library and information congress: 74th IFLA general conference and council, 10-14 August 2008, Québec, Canada. Vgl. auch: http://www.ibiblio.org/fred2.0/wordpress/?p=20 (mit Grafik der Beziehung zwischen 'mammal' und 'doorbell')

0.0011898145 = product of:
  0.004759258 = sum of:
    0.004759258 = weight(_text_:information in 1832) [ClassicSimilarity], result of:
      0.004759258 = score(doc=1832,freq=2.0), product of:
        0.06134496 = queryWeight, product of:
          1.7554779 = idf(docFreq=20772, maxDocs=44218)
          0.034944877 = queryNorm
        0.0775819 = fieldWeight in 1832, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          1.7554779 = idf(docFreq=20772, maxDocs=44218)
          0.03125 = fieldNorm(doc=1832)
  0.25 = coord(1/4)

Theme

Information Gateway