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Titlebook: Scientific and Statistical Database Management; 24th International C Anastasia Ailamaki,Shawn Bowers Conference proceedings 2012 Springer-V

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51#
發(fā)表于 2025-3-30 10:35:52 | 只看該作者
Substructure Clustering: A Novel Mining Paradigm for Arbitrary Data Types.In this work, we unify and generalize existing substructure mining tasks to the novel paradigm of substructure clustering that is applicable to data of an arbitrary type. As a proof of concept showing the feasibility of our novel paradigm, we present a specific instantiation for the task of .. By i
52#
發(fā)表于 2025-3-30 15:37:56 | 只看該作者
0302-9743 rnational Conference on Scientific and Statistical Database Management, SSDBM 2012, held in Chania, Grete, Greece, in June 2012. The 25 long and 10 short papers presented together with 2 keynotes, 1 panel, and 13 demonstration and poster papers were carefully reviewed and selected from numerous subm
53#
發(fā)表于 2025-3-30 17:22:42 | 只看該作者
Conference proceedings 2012 papers were carefully reviewed and selected from numerous submissions. The topics covered are uncertain and probabilistic data, parallel and distributed data management, graph processing, mining multidimensional data, provenance and workflows, processing scientific queries, and support for demanding applications.
54#
發(fā)表于 2025-3-30 21:40:34 | 只看該作者
55#
發(fā)表于 2025-3-31 04:11:36 | 只看該作者
Efficient Range Queries over Uncertain Stringsive distribution functions and local perturbation to improve lower bounds and upper bounds. Comprehensive experiment results show that our filter-based scheme, in the uncertain settings, is more efficient than existing methods only leveraging cumulative distribution functions or local perturbation.
56#
發(fā)表于 2025-3-31 07:37:43 | 只看該作者
57#
發(fā)表于 2025-3-31 09:13:58 | 只看該作者
58#
發(fā)表于 2025-3-31 14:43:16 | 只看該作者
Efficient Similarity Search in Very Large String Sets SSI’s space consumption can be gracefully traded against search time..We evaluated SSI on different sets of person names with up to 170?million strings from a social network and compared it to other state-of-the-art methods. We show that in the majority of cases, SSI is significantly faster than other tools and requires less index space.
59#
發(fā)表于 2025-3-31 20:47:37 | 只看該作者
Navigating Oceans of Datae commonly, big data implies a big variety of data sources. For example, the Center for Coastal Margin Observation and Prediction (CMOP) has multiple kinds of sensors (salinity, temperature, pH, dissolved oxygen, chlorophyll A & B) on diverse platforms (fixed station, buoy, ship, underwater robot) c
60#
發(fā)表于 2025-3-31 22:43:42 | 只看該作者
Probabilistic Range Monitoring of Streaming Uncertain Positions in GeoSocial Networks a varying degree of uncertainty in order to protect their privacy. We aim to effectively provide instant response to multiple user requests, each focusing at continuously monitoring possible presence of their friends or followers in a time-varying region of interest. Every continuous range query mu
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