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Gödert, W.: Inhaltliche Dokumenterschließung, Information Retrieval und Navigation in Informationsräumen (1995) 0.10

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Abstract: Examines the advantages and disadvantages of precoordinated, postcoordinated and automatic indexing with regard to existing information storage systems, such as card catalogues, OPACs, CR-ROM databases, and online databases. Presents a general model of document content representation and concludes that the library profession needs to address the development of databank design models, relevance feedback methods and automatic indexing assessment methods, to make indexing more effective
Theme: Semantisches Umfeld in Indexierung u. Retrieval

Baofu, P.: ¬The future of information architecture : conceiving a better way to understand taxonomy, network, and intelligence (2008) 0.09

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LCSH: Information storage and retrieval systems
RSWK: Suchmaschine / Information Retrieval
Subject: Information storage and retrieval systems
Suchmaschine / Information Retrieval
Theme: Semantisches Umfeld in Indexierung u. Retrieval

Morato, J.; Llorens, J.; Genova, G.; Moreiro, J.A.: Experiments in discourse analysis impact on information classification and retrieval algorithms (2003) 0.07
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Abstract

Researchers in indexing and retrieval systems have been advocating the inclusion of more contextual information to improve results. The proliferation of full-text databases and advances in computer storage capacity have made it possible to carry out text analysis by means of linguistic and extra-linguistic knowledge. Since the mid 80s, research has tended to pay more attention to context, giving discourse analysis a more central role. The research presented in this paper aims to check whether discourse variables have an impact on modern information retrieval and classification algorithms. In order to evaluate this hypothesis, a functional framework for information analysis in an automated environment has been proposed, where the n-grams (filtering) and the k-means and Chen's classification algorithms have been tested against sub-collections of documents based on the following discourse variables: "Genre", "Register", "Domain terminology", and "Document structure". The results obtained with the algorithms for the different sub-collections were compared to the MeSH information structure. These demonstrate that n-grams does not appear to have a clear dependence on discourse variables, though the k-means classification algorithm does, but only on domain terminology and document structure, and finally Chen's algorithm has a clear dependence on all of the discourse variables. This information could be used to design better classification algorithms, where discourse variables should be taken into account. Other minor conclusions drawn from these results are also presented.

Theme

Semantisches Umfeld in Indexierung u. Retrieval

Gao, J.; Zhang, J.: Clustered SVD strategies in latent semantic indexing (2005) 0.06

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Abstract: The text retrieval method using latent semantic indexing (LSI) technique with truncated singular value decomposition (SVD) has been intensively studied in recent years. The SVD reduces the noise contained in the original representation of the term-document matrix and improves the information retrieval accuracy. Recent studies indicate that SVD is mostly useful for small homogeneous data collections. For large inhomogeneous datasets, the performance of the SVD based text retrieval technique may deteriorate. We propose to partition a large inhomogeneous dataset into several smaller ones with clustered structure, on which we apply the truncated SVD. Our experimental results show that the clustered SVD strategies may enhance the retrieval accuracy and reduce the computing and storage costs.
Theme: Semantisches Umfeld in Indexierung u. Retrieval

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