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Titlebook: Database and Expert Systems Applications; 23rd International C Stephen W. Liddle,Klaus-Dieter Schewe,Xiaofang Zho Conference proceedings 20

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Towards Quantitative Constraints Ranking in Data Clusteringity of the generated clusters. However, in some real problems, an explosion in the volume of the processed data and their related constraints overwhelm the expert. In this paper, we aim to explicitly formulate the expert preferences on supervising the clustering mechanism through injecting their deg
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A Topic-Oriented Analysis of Information Diffusion in a Blogosphere very important in developing successful business strategies for a blogosphere. In this paper, we discuss how to predict information diffusion in a blogosphere. Documents diffused over a blogosphere deal with information on . in reality. However, previous studies of information diffusion did not con
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Trip Tweets Search by Considering Spatio-temporal Continuity of User Behaviorher people as a whole experience. In this paper, we propose a novel method to find and organize such fragmented tweets at the level of user experiences. The notable feature of our method is that we find and organize tweets related to a certain trip experience by considering the spatio-temporal conti
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https://doi.org/10.1007/978-3-642-32597-7Web mining; machine learning; performance evaluation; recommender systems; social Web
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978-3-642-32596-0Springer-Verlag Berlin Heidelberg 2012
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Stephen W. Liddle,Klaus-Dieter Schewe,Xiaofang ZhoFast track conference proceedings.Unique visibility.State of the art research
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The Origins and Early Development of CPEveral relational databases. In our scenario, we assume that the databases involved are updated by external independent applications, possibly introducing inconsistencies in a particular database, or leading to inconsistency among the subset of databases that refer to the same data. Argumentation rea
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Competencies – Longer Term Use & Developmentuse of light-weight query-driven analysis methods, as opposed to heavy-weight schemes that optimize for speed at the expense of size. This paper is an attempt in the direction of query processing over losslessly compressed scientific data. We propose a co-designed double-precision compression and in
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