Search (4 results, page 1 of 1)

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Abstract

This paper is about a better understanding of the structure and dynamics of science and the usage of these insights for compensating the typical problems that arises in metadata-driven Digital Libraries. Three science model driven retrieval services are presented: co-word analysis based query expansion, re-ranking via Bradfordizing and author centrality. The services are evaluated with relevance assessments from which two important implications emerge: (1) precision values of the retrieval services are the same or better than the tf-idf retrieval baseline and (2) each service retrieved a disjoint set of documents. The different services each favor quite other - but still relevant - documents than pure term-frequency based rankings. The proposed models and derived retrieval services therefore open up new viewpoints on the scientific knowledge space and provide an alternative framework to structure scholarly information systems.

Theme

Semantisches Umfeld in Indexierung u. Retrieval

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Abstract

The paper proposes three different kinds of science models as value-added services that are integrated in the retrieval process to enhance retrieval quailty. The paper discusses the approaches Search Term Recommendation, Bradfordizing and Author Centrality on a general level and addresses implementation issues of the models within a real-life retrieval environment.

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Abstract

We present the TREC Open Search track, which represents a new evaluation paradigm for information retrieval. It offers the possibility for researchers to evaluate their approaches in a live setting, with real, unsuspecting users of an existing search engine. The first edition of the track focuses on the academic search domain and features the ad-hoc scientific literature search task. We report on experiments with three different academic search engines: Cite-SeerX, SSOAR, and Microsoft Academic Search.

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Abstract

Automatic content indexing is one of the innovations that are increasingly changing the way libraries work. In theory, it promises a cataloguing service that would hardly be possible with humans in terms of speed, quantity and maybe quality. The German National Library (DNB) has also recognised this potential and is increasingly relying on the automatic indexing of their catalogue content. The DNB took a major step in this direction in 2017, which was announced in two papers. The announcement was rather restrained, but the content of the papers is all the more explosive for the library community: Since September 2017, the DNB has discontinued the intellectual indexing of series Band H and has switched to an automatic process for these series. The subject indexing of online publications (series O) has been purely automatical since 2010; from September 2017, monographs and periodicals published outside the publishing industry and university publications will no longer be indexed by people. This raises the question: What is the quality of the automatic indexing compared to the manual work or in other words to which degree can the automatic indexing replace people without a signi cant drop in regards to quality?