Titlebook: Big Data Analytics and Knowledge Discovery; 17th International C Sanjay Madria,Takahiro Hara Conference proceedings 2015 Springer Internati

Bravado

Functional Programming Overviewwever incurs security and privacy issues. To address the issues, this paper proposes two protocols for mining frequent patterns securely on the cloud by employing fully homomorphic encryption. One protocol requires little communication between the client and the cloud service provider, the other inc

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https://doi.org/10.1007/978-1-4842-1031-4d decision making in data analytics processes. This paper investigates how to build discrimination-aware models even when the available training set is intrinsically discriminating based on some sensitive attributes, such as race, gender or personal status. We propose a new classification method cal

AUGUR

https://doi.org/10.1007/978-3-030-67626-1s of these big data. Users (or social entities) in these social networks are often linked by some interdependency such as friendship or “following” relationships. As these big social networks keep growing, there are situations in which individual users or businesses want to find those frequently fol

zonules

The 3 A’s of a Machine Learning Projectety of topics. As social networks and microblogging services become more popular, the need to mine and analyze their content grows. We study the task of sentiment analysis in the well-known social network Twitter (.). We present a case study on tweets written in Greek and propose an effective method

ALT

Christopher M. Rosett,Austin Hagertye Data extraction are either template-dependent or they are limited to comment-posting-structure discovery. We are not aware of any technique that extracts the detailed comment information like comment text, commenter and discussion structure from the comment page. In this paper, we present a templa

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Christopher M. Rosett,Austin Hagertyneous network into a homogeneous network before applying a similarity measure. However, such transformation results in information loss as path semantics are lost. In this paper, we study the problem of measuring relatedness between objects in a heterogeneous network using only link information and

俗艳

High Availability in a Sandbox,y pair of entities. We present an approach to querying for similar individuals across multiple ontologies that makes use of the correspondences discovered during ontology alignment in order to reduce this cost. The query algorithm is designed using the framework of fuzzy logic and extends fuzzy onto

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Introduction to High Availability,se of heterogeneity issues and sparsity of data. In this paper we present a semantics-based approach for dynamic calculation of PIs in the context of sparse distributed data marts. In particular, we propose to enrich the multidimensional model with the formal description of the structure of an indic