By Markus Helfert, Andreas Holzinger, Orlando Belo, Chiara Francalanci

This e-book constitutes the completely refereed lawsuits of the Fourth overseas convention on information applied sciences and functions, facts 2015, held in Colmar, France, in July 2015.

The nine revised complete papers have been rigorously reviewed and chosen from 70 submissions. The papers take care of the next themes: databases, facts warehousing, info mining, facts administration, information safety, wisdom and data structures and applied sciences; complex program of data.

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Additional resources for Data Management Technologies and Applications: 4th International Conference, DATA 2015, Colmar, France, July 20-22, 2015, Revised Selected Papers

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T. the artworks is discussed in [1]. 4 Experiments on Data Classification The experiments described in this Section were carried out from a dataset of 253 log files, one for each visitor of the exhibition. Experiments have been executed exploiting the computing resources provided by CRESCO/ENEAGRID High Performance Computing infrastructure [4]. We have tracked the visitor behaviour by using a suitable Extrapolation Algorithm (EA), which has a JSON file as input data. 5% ... 259 Path is followed : True ------------------------------------...

Among other schemes cited in the study is Weighted Log Likelihood Ratio, whose per-class value can be computed as wllr(ti , ck ) = A · log A+B A(C + D) C(A + B) . (17) Many of the same schemes are reviewed in [14] and tested with multiple learning algorithms. Here are also proposed more trivial schemes which are shown to perform well, such as the maximum class density, defined as cdM AX (ti ) = max cd(ti , ck ), ck ∈C where cd(ti , ck ) = A . A+C (18) In [29] is addressed the so-called over-weighting problem, where the weighting scheme erroneously attributes excessive importance to rare (singular ) terms: a regularization method applicable to existing schemes is proposed as a solution.

Concept maps construction based on exhaustive rules and vector space intersection. IJCSNS 14(7), 26 (2014) 14. , A latent semantic approach to xml clustering by content and structure based on non-negative matrix factorization. In: 2013 12th International Conference on Machine Learning and Applications (ICMLA) IEEE 2013, vol. 1, pp. 179−184 (2013) 15. : Latent semantic analysis. Wiley Interdisc. : Cognitive Sci. 4(6), 683–692 (2013) 16. : Semantic Web for the Working Ontologist, 2nd edn. it Abstract.

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