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Titlebook: Database Systems for Advanced Applications; 21st International C Shamkant B. Navathe,Weili Wu,Hui Xiong Conference proceedings 2016 Springe

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发表于 2025-3-21 18:43:30 | 显示全部楼层 |阅读模式
书目名称Database Systems for Advanced Applications
副标题21st International C
编辑Shamkant B. Navathe,Weili Wu,Hui Xiong
视频video
概述Includes supplementary material:
丛书名称Lecture Notes in Computer Science
图书封面Titlebook: Database Systems for Advanced Applications; 21st International C Shamkant B. Navathe,Weili Wu,Hui Xiong Conference proceedings 2016 Springe
描述.This two volume set LNCS 9642 and LNCS 9643 constitutes the refereed proceedings of the 21st International Conference on Database Systems for Advanced Applications, DASFAA 2016, held in Dallas, TX, USA, in April 2016...The 61 full papers presented were carefully reviewed and selected from a total of 183 submissions. The papers cover the following topics: crowdsourcing, data quality, entity identification, data mining and machine learning, recommendation, semantics computing and knowledge base, textual data, social networks, complex queries, similarity computing, graph databases, and miscellaneous, advanced applications..
出版日期Conference proceedings 2016
关键词Big data; Data mining and knowledge discovery; Database management; Evolutionary machine learning; Infor
版次1
doihttps://doi.org/10.1007/978-3-319-32049-6
isbn_softcover978-3-319-32048-9
isbn_ebook978-3-319-32049-6Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightSpringer International Publishing Switzerland 2016
The information of publication is updating

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https://doi.org/10.1007/978-3-319-32049-6Big data; Data mining and knowledge discovery; Database management; Evolutionary machine learning; Infor
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Intentions and the Doctrine of Double Effectlarity search, entity profiling and linkage. Most existing work focus on using the main features common to all. While this approach makes sense in settings where commonality is of primary interest, there are many scenarios as important where uncommon and discriminative features are more useful. To a
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Oren Asman,Yechiel Michael Barilantopic or event prediction models have been proposed in the past few years, researches that focus on the single tweet prediction just emerge recently. In this paper, we propose STH-Bass, a Spatial and Temporal Heterogeneous Bass model derived from economic field, to predict the popularity of a single
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Palgrave European Film and Media Studiesgregation queries on a set of lists plays an increasingly important role in these domains. Unfortunately the existing solutions, such as threshold-style (TA-style) algorithms, do not guarantee superior performance on a large number of lists. In this paper, we introduce a merge-based strategy, called
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https://doi.org/10.1007/978-3-319-89827-8onnecting nodes through a sequence of heterogeneous edges, representing different kinds of semantic relations among nodes. Meta-paths are good mechanisms to improve the quality of graph analysis on heterogeneous information networks. This paper presents an iceberg cube framework for heterogeneous in
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https://doi.org/10.1007/978-3-319-89827-8ived significant research attention in the past few years. However, we realise that the state-of-the-art algorithm, SLICE, accesses many objects that do not contribute to its . results when running the filtering phase, which deteriorates the query performance. In this paper, we propose a novel R.NN
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