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Järvelin, K.; Kristensen, J.; Niemi, T.; Sormunen, E.; Keskustalo, H.: ¬A deductive data model for query expansion (1996) 0.02

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Abstract: We present a deductive data model for concept-based query expansion. It is based on three abstraction levels: the conceptual, linguistic and occurrence levels. Concepts and relationships among them are represented at the conceptual level. The expression level represents natural language expressions for concepts. Each expression has one or more matching models at the occurrence level. Each model specifies the matching of the expression in database indices built in varying ways. The data model supports a concept-based query expansion and formulation tool, the ExpansionTool, for environments providing heterogeneous IR systems. Expansion is controlled by adjustable matching reliability.
Source: Proceedings of the 19th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (ACM SIGIR '96), Zürich, Switzerland, August 18-22, 1996. Eds.: H.P. Frei et al
Type: a

Kristensen, J.; Järvelin, K.: ¬The effectiveness of a searching thesaurus in free-text searching in a full-text database (1990) 0.00

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Type: a

Järvelin, K.; Vakkari, P.: ¬The evolution of library and information science 1965-1985 : a content analysis of journal titles (1993) 0.00

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Type: a

Järvelin, K.; Niemi, T.: Deductive information retrieval based on classifications (1993) 0.00
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Abstract

Modern fact databses contain abundant data classified through several classifications. Typically, users msut consult these classifications in separate manuals or files, thus making their effective use difficult. Contemporary database systems do little support deductive use of classifications. In this study we show how deductive data management techniques can be applied to the utilization of data value classifications. Computation of transitive class relationships is of primary importance here. We define a representation of classifications which supports transitive computation and present an operation-oriented deductive query language tailored for classification-based deductive information retrieval. The operations of this language are on the same abstraction level as relational algebra operations and can be integrated with these to form a powerful and flexible query language for deductive information retrieval. We define the integration of these operations and demonstrate the usefulness of the language in terms of several sample queries

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