Transactions on Large-Scale Data- and Knowledge-Centered Systems XLIX - Info and Reading Options

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Intro -- Preface -- Organization -- Contents -- Temporal Aggregation of Spanning Event Stream: An Extended Framework to Handle the Many Stream Models -- 1 Introduction -- 2 Formal Background -- 2.1 About Time -- 2.2 Spanning Event Stream -- 2.3 Temporal Windowing -- 2.4 Aggregation -- 3 Assigning Spanning Events to Temporal Windows -- 3.1 Adaptation of Point Event Windows to Spanning Events -- 3.2 Additional Parameters -- 3.3 Time-Based Sliding and Tumbling Windows -- 3.4 Session Windows -- 4 Processing Spanning Event Stream -- 4.1 Supporting Structures and Operations -- 4.2 Time-Based Sliding and Tumbling Windows -- 4.3 Session Windows -- 5 Experiments -- 6 Related Work -- 7 Conclusion and Future Work -- References -- Reducing the Cost of Aggregation in Crowdsourcing -- 1 Introduction -- 2 Preliminaries -- 2.1 Factors Influencing Efficiency of Crowdsourcing -- 2.2 Expectation Maximization -- 3 The Aggregation Model -- 3.1 Aggregating Answers -- 4 Cost Model -- 5 Experiments -- 6 Spammer Detection -- 6.1 Spammers Models -- 6.2 Experimentation of CrowdInc with Spammers -- 6.3 Spammer Detection with Thresholds -- 6.4 Effect of Spammers on Accuracy -- 6.5 Effect of Spammers on Costs -- 7 Conclusion and Discussions -- References -- A Partitioning Approach for Skyline Queries in Presence of Partial and Dynamic Orders -- 1 Introduction -- 2 Preliminaries -- 3 dySky Algorithm -- 3.1 Single Partial and Dynamic Dimension -- 3.2 Multiple Partial and Dynamic Dimensions -- 4 Optimization Using Materialization -- 4.1 Materialization Structure -- 4.2 Full Materialization -- 4.3 Constrained Materialization -- 5 Related Work -- 5.1 Techniques for Totally Ordered Data -- 5.2 Techniques for Data with Dynamic Partial Orders -- 6 Experiments -- 6.1 Query Answering Time -- 6.2 Precomputation Time and Storage -- 6.3 Caching Queries

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