By Jiawei Han (auth.), Stefano Spaccapietra, Fred Maryanski (eds.)

Searching for Semantics: facts Mining, opposite Engineering Stefano Spaccapietra Fred M aryanski Swiss Federal Institute of know-how collage of Connecticut Lausanne, Switzerland Storrs, CT, united states assessment AND destiny instructions within the previous few years, database semantics study has became sharply from a hugely theoretical area to at least one with extra specialize in sensible features. The DS- 7 operating convention held in October 1997 in Leysin, Switzerland, demon­ strated the extra pragmatic orientation of the present new release of prime researchers. The papers offered on the assembly emphasised the 2 significant parts: the invention of semantics and semantic info modeling. The paintings within the latter classification shows that even though object-oriented database administration structures have emerged as commercially achievable prod­ ucts, many primary modeling matters require extra research. trendy object-oriented platforms give you the power to explain advanced items and comprise options for mapping from a relational database to things. although, we needs to extra discover the expression of data concerning the dimensions of time and area. Semantic types own the richness to explain structures containing spatial and temporal facts. The problem of in­ corporating those gains in a fashion that promotes effective manipulation by way of the topic expert nonetheless calls for huge development.

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Extra resources for Data Mining and Reverse Engineering: Searching for semantics. IFIP TC2 WG2.6 IFIP Seventh Conference on Database Semantics (DS-7) 7–10 October 1997, Leysin, Switzerland

Example text

Thus, efficiency of computation can easily be achieved for such programs, while optimization becomes more and more needed (and difficult) if more expressive queries are posed. 2 An example of Rule Evaluation We shall now briefly comment on how FastComp can be used, at least in principle, to execute a WG-log query. Our sample query execution is based on three data structures: • the (Typed) Adiacency Matrix TAM of the instance graph. • the Instance Table IT linking schema entities and their instances • the URL list UL linking instances to HTML pages or other network objects.

13 does not show such a matrix, but a simpler, binary matrix where each entry i, j is 1 whenever instances i and j are linked by a navigational step, a logical relationships or both. Moreover, rows and columns pertaining to slots are not listed. Actually, we do not need to store slots in the TAM matrix; it is sufficient and surely less space-consuming to store them in auxiliary data structures pertaining to each single entity, in order to allow fast label matching. 14) associates the unique code of each schema entity to a list of unique numbers called instance identifiers; this allows the Query Manager to trace instances of schema-defined entities in the instance graph.

This paper is organized as follows: 26 Part One Invited Talks WebqucryapproM:be$ Figure 3 A semantics-based classification of research approaches to WWW querying Section 2 presents a survey of existing techniques, Sections 3 and 4 describe the data model and language of WG-Iog; Section 5 presents the naive computation of WG-Iog queries, while Section 6 draws the conclusions and outlines future research on the same subject. 2 RELATED WORK The huge amount of data published via the World Wide Web has led to a number of research efforts on techiques to index, query and restructure WWW sites contents.

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