Titlebook: Machine Learning and Knowledge Extraction; First IFIP TC 5, WG Andreas Holzinger,Peter Kieseberg,Edgar Weippl Conference proceedings 2017

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Some Remarks on the Algebraic Properties of Group Invariant Operators in Persistent Homologyient data comparison. In particular, persistent topology and homology are relevant mathematical tools in TDA, and their study is attracting more and more researchers. As a matter of fact, in many applications data can be represented by continuous real-valued functions defined on a topological space

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Decentralized Computation of Homology in Wireless Sensor Networks Using Spanning Treesometric position and orientation of individual nodes is not known, useful information on coverage can still be deduced based on connectivity data. In recent years, homological criteria have been introduced to verify complete signal coverage, given only the network communication graph. However, their

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Detecting and Ranking API Usage Pattern in Large Source Code Repository: A LFM Based Approachmework and library APIs fail in providing sufficient and adequate code examples in corresponding official documentations. Thus, it takes great programmers’ efforts to browse and extract API usage examples from websites. To reduce such effort, this paper proposes a graph-based pattern-oriented mining

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Managing Complexity: Towards Intelligent Error-Handling Assistance Trough Interactive Alarm Flood Re. Especially the search for the root cause of cascading failures becomes highly time-consuming. Within this paper, we address the question on how to help human users to better and faster understand root causes of such situations. We propose a concept of interactive alarm flood reduction and present

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Decision Tree Rule Induction for Detecting Covert Timing Channels in TCP/IP Traffic are able to circumvent security barriers, compromise systems, and facilitate data leakage. A set of statistical methods called DAT (Descriptive Analytics of Traffic) has been previously proposed as a general approach for detecting covert channels. In this paper, we implement and evaluate DAT detect

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Practical Estimation of Mutual Information on Non-Euclidean Spacesefore” and “after”. The proposed approach focuses therefore on data usability, more than in ensuring that the data is sufficiently anonymized. We use Mutual Information as the measure criterion for this approach, and detail how we propose to measure Mutual Information over non-Euclidean data, in pra

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