New PDF release: Advances in Databases and Information Systems

By Piotr Andruszkiewicz (auth.), Tadeusz Morzy, Theo Härder, Robert Wrembel (eds.)

This quantity is the second of the sixteenth East-European convention on Advances in Databases and data structures (ADBIS 2012), hung on September 18-21, 2012, in Poznań, Poland. the 1st one has been released within the LNCS sequence.

This quantity comprises 27 examine contributions, chosen out of ninety. The contributions conceal a large spectrum of issues within the database and knowledge structures box, together with: database origin and concept, info modeling and database layout, enterprise technique modeling, question optimization in relational and item databases, materialized view choice algorithms, index info buildings, disbursed platforms, procedure and information integration, semi-structured info and databases, semantic facts administration, info retrieval, facts mining suggestions, info circulate processing, belief and acceptance within the web, and social networks. therefore, the content material of this quantity covers the examine parts from basics of databases, via nonetheless sizzling subject study difficulties (e.g., information mining, XML info processing), to novel examine parts (e.g., social networks, belief and attractiveness, and knowledge movement processing). The editors of this quantity think that its content material will encourage the researchers with new rules for destiny improvement. it might additionally function an summary of the continued paintings within the box of databases and data systems.

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In this paper we introduce a new method based on iCPI-tree materialization and a spatial partitioning to efficiently discover collocation patterns. We have implemented this new solution and conducted series of experiments. The results show a significant improvement in processing times both on synthetic and real world datasets. 1 Introduction Spatial data mining [6] is a research field that aims at discovery of regularities hidden in huge spatial datasets. One of the possible types of such regularities is called a spatial collocation pattern (a collocation in short).

J. ) SSTD 2001. LNCS, vol. 2121, pp. 236–256. Springer, Heidelberg (2001) 7. : Efficient Discovery of Spatial Co-Location Patterns Using the iCPI-tree. The Open Information Systems Journal 3(2), 69–80 (2009) 8. : A New Join-less Approach for Co-location Pattern Mining. L. ) CIT, pp. 197– 202. IEEE, Sydney (2008) 9. : An Order-clique-based Approach for Mining Maximal Co-locations. Inf. Sci. 023 10. : Data mining query scheduling for apriori common counting. In: Barzdins, J. ) Proceedings of the Sixth International Baltic Conference on Databases and Information Systems (DB&IS 2004).

J,k set containing exactly w ∈ N associations between classes eIO and eOO The corresponding to the input and output objects io j and iok , respectively, is: ROO j,k (a) (l) (l) ROO j,k (a) = rOO ∈ R rOO = TOO io j , i f j , a, o f k , ook , l = 1, . . , w , Towards the Automated Business Model-Driven Conceptual Database Design 39 where the basic TOO rule, that maps a SISO tuple io, i f , a, o f , oo into binary association rOO between corresponding classes, is given with: de f TOO io, i f , a, o f , oo = rOO name(rOO ) = name(a) ∧ memberEnd(rOO ) = {source,target} | type(source) = eIO ∧ multiplicity(source) = ms ∧ type(target) = eOO ∧ multiplicity(target) = mt .

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