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Titlebook: Database Systems for Advanced Applications; 24th International C Guoliang Li,Jun Yang,Yongxin Tong Conference proceedings 2019 Springer Nat

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發(fā)表于 2025-3-21 19:36:23 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書目名稱Database Systems for Advanced Applications
副標(biāo)題24th International C
編輯Guoliang Li,Jun Yang,Yongxin Tong
視頻videohttp://file.papertrans.cn/264/263419/263419.mp4
叢書名稱Lecture Notes in Computer Science
圖書封面Titlebook: Database Systems for Advanced Applications; 24th International C Guoliang Li,Jun Yang,Yongxin Tong Conference proceedings 2019 Springer Nat
描述.This two-volume set LNCS 11446 and LNCS 11447 constitutes the refereed proceedings of the 24th International Conference on Database Systems for Advanced Applications, DASFAA 2019, held in Chiang Mai, Thailand, in April 2019...The 92 full papers and 64 short papers were carefully selected from a total of 501 submissions. In addition, 13 demo papers and 6 tutorial papers are included. The full papers are organized in the following topics: big data; clustering and classification; crowdsourcing; data integration; embedding; graphs; knowledge graph; machine learning; privacy and graph; recommendation; social network; spatial; and spatio-temporal. The short papers, demo papers, and tutorial papers can be found in the volume LNCS 11448, which also includes the workshops of DASFAA 2019..
出版日期Conference proceedings 2019
關(guān)鍵詞artificial intelligence; computational linguistics; computer networks; data mining; data stream; image pr
版次1
doihttps://doi.org/10.1007/978-3-030-18576-3
isbn_softcover978-3-030-18575-6
isbn_ebook978-3-030-18576-3Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightSpringer Nature Switzerland AG 2019
The information of publication is updating

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A Frequency Scaling Based Performance Indicator Framework for Big Data Systemsn misleading and incomparable with each other. In this paper, a novel indicator framework which can directly compare the impact of different indicators with each other is proposed to identify and analyze the performance bottleneck efficiently. A methodology which can construct the indicator from the
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A Time-Series Sockpuppet Detection Method for Dynamic Social Relationshipssors. Current works are continually making efforts to detect sockpuppets based on verbal, non-verbal or network-structure features. Network structure has attracted much attention, while the time series dynamic characteristic of sockpuppet network has not been considered. With our observation, after
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HSDS: An Abstractive Model for Automatic Survey Generationend of the specific area. As far as we know, the most relevant study with automatic survey generation is the task of automatic related work generation. Almost all existing methods of automatic related work generation extract the important sentences from multiple relevant papers to assemble a related
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Discovering Relationship Patterns Among Associated Temporal Event Sequences analysis, and banking transaction analysis. Contrast sequence data mining is useful in describing the differences between two sets (classes) of sequences. However, in prior studies, little work has been done in how to mine the patterns from sequences formed by associated temporal events, where ther
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