archenemy 发表于 2025-3-23 12:46:01
Conference proceedings 2016bmissions...the focus of the conference was on following subjects: ...Spatio-temporal,Textual and Multimedia Data Management..Social Media Data Analysis..Modellingand Learning with Big Data..Streamingand Real-time Data Analysis..Recommendation System..Data Quality and Privacy..QueryOptimization and Scalable Data Processing. .ARCH 发表于 2025-3-23 15:19:00
Flexible and Adaptive Stream Join Algorithm model on distributed stream joins and supports arbitrary join predicates. It can handle data skew perfectly since it randomly routes tuples to cells with each steam corresponding to one side of the matrix. Designing of the partitioning scheme of the matrix is a determining factor to maximize system消极词汇 发表于 2025-3-23 19:39:38
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Flexible and Adaptive Stream Join Algorithm model on distributed stream joins and supports arbitrary join predicates. It can handle data skew perfectly since it randomly routes tuples to cells with each steam corresponding to one side of the matrix. Designing of the partitioning scheme of the matrix is a determining factor to maximize systemFeature 发表于 2025-3-24 13:28:00
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A Workload-Driven Vertical Partitioning Approach Based on Streaming Frameworkement for large scale OLTP and OLAP applications. Horizontal and vertical database partitioning can improve the performance and manageability for shared-nothing systems which are popular in nowadays. However, the existing partitioning techniques can’t deal with dynamic information efficiently and ca引导 发表于 2025-3-25 01:50:31
A Target-Dependent Sentiment Analysis Method for Micro-blog Streamsdependent sentiment analysis methods can not get acceptable accuracy. Recently some new sentiment analysis methods using Recursive Neural Networks (RNN) are promissing but they are not target-dependent. In this paper we propose a target-dependent sentiment analysis method for micro-blog streams base