By Witold Abramowicz, Angelika Kokkinaki
This ebook comprises the refereed lawsuits of the seventeenth foreign convention on company details structures, BIS 2014, held in Larnaca, Cyprus, in may well 2014. The BIS convention sequence follows traits in educational and company examine; hence, the subject matter of the BIS 2014 convention was once “Big info: difficulties Solved and ultimate Challenges.” presently, large information is likely one of the such a lot sought after tendencies in parts resembling suggestion engines, fraud detection, chance modeling, campaign and social community analysis.
The 22 revised complete papers have been conscientiously reviewed and chosen from fifty eight submissions. they're grouped into sections on enormous info, enterprise strategy administration, ontologies and conceptual modeling, collaboration, carrier technology and interoperability and particular BIS applications.
Read Online or Download Business Information Systems: 17th International Conference, BIS 2014, Larnaca, Cyprus, May 22-23, 2014. Proceedings PDF
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Additional info for Business Information Systems: 17th International Conference, BIS 2014, Larnaca, Cyprus, May 22-23, 2014. Proceedings
3. Another option could be to use association rule mining to deduce decision rules. Yet, this option lacks comprehensibility for the user. In addition, from a more technical point of view, since only association rules related to the metric attribute are relevant, computing all frequent item sets as commonly done in association rule discovery seems to be superfluous. Recommendation generation encompasses the four sequential steps described in the following, namely definition of the data basis, mining model generation, mining model analysis and recommendation processing (see Fig.
Gilani description of similarity metric used within D-HS. The last part describes the indexing structure, which provide eﬃcient and accurate retrieval of similar cases for the speciﬁed target. 1 Case The representation of the ADE case is shown in ﬁgure 2. Fig. 2. A case representation The case combines problem description attributes and solution attributes. The problem description attributes are used to identify case features, which are used during the indexing and retrieval processes. , treatments (a combination of conditions and prescribed medications).
The proposed indexing technique described in the next section, avoids such a routine search and makes the retrieval process more eﬃcient. N lx ly L − 1) ∧ P (lx , cix ) ∧ P (lx , qx )} L − 1) ∧ P (ly , ciy ) ∧ P (ly , qy )} , (6) where P (l, x) is a predicate (7), which is true if the tested attribute x lies within the container with the index l and false otherwise: P (l, x) = (lΔδ x) ∧ (x < (l + 1)Δδ)), (7) 1 where the interval width is deﬁned as Δδ = . L All dimensions for mapping case attributes are split into L intervals.