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Abstract

The role of linguistics in information access, extraction and dissemination is essential. Radical changes in the techniques of information and communication at the end of the twentieth century have had a significant effect on the function of the linguistic paradigm and its applications in all forms of communication. The introduction of new technical means have deeply changed the possibilities for the distribution of information. In this situation, what is the role of the linguistic paradigm and its practical applications, i.e., natural language processing (NLP) techniques when applied to information access? What solutions can linguistics offer in human computer interaction, extraction and management? Many fields show the relevance of the linguistic paradigm through the various technologies that require NLP, such as document and message understanding, information detection, extraction, and retrieval, question and answer, cross-language information retrieval (CLIR), text summarization, filtering, and spoken document retrieval. This paper focuses on the central role of human language technologies in the information society, surveys the current situation, describes the benefits of the above mentioned applications, outlines successes and challenges, and discusses solutions. It reviews the resources and means needed to advance information access and dissemination across language boundaries in the twenty-first century. Multilingualism, which is a natural result of globalization, requires more effort in the direction of language technology. The scope of human language technology (HLT) is large, so we limit our review to applications that involve multilinguality.

Content

Beitrag eines Themenheftes "Knowledge organization and classification in international information retrieval"

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Abstract

In this paper we briefly sketch the dynamics of the linguistic paradigm in Information Retrieval (IR) and its adaptation to the Internet. The emergence of Natural Language Processing (NLP) techniques has been a major factor leading to this adaptation. These techniques and tools try to adapt to the current needs, i.e. retrieving information from documents written and indexed in a foreign language by using a native language query to express the information need. This process, known as cross-language IR (CLIR), is a field at the cross roads of both Machine Translation and IR. This field represents a real challenge to the IR community and will require a solid cooperation with the NLP community.