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010 $a1-281-91906-3
010 $a9786611919061
010 $a981-277-024-0
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100 $a20090129d2007 uy 0
101 0 $aeng
135 $aur|n|---|||||
181 $ctxt
182 $cc
183 $acr
200 10$aAdvances in scalable web information integration and service$b[electronic resource] $eproceedings of DASFAA2007 International Workshop on Scalable Web Information Integration and Service (SWIIS2007), Bangkok, Thailand, 9-12 April 2007 /$feditors, Yoshifumi Masunaga ... [et al.]
210 $aNew Jersey $cWorld Scientific$dc2007
215 $a1 online resource (128 p.)
300 $a"This first workshop was organized in conjunction with the 12th International Conference on Database Systems for Advanced Applications (DASFAA2007) held in Bangkok, Thailand."--P. vii.
311 $a981-277-023-2
320 $aIncludes bibliographical references and index.
327 $aTable of Contents; Preface; Invited Session; Using Semantics in XML Data Management Tok Wang Ling and Gillian Dobbie; 1. Introduction; 2. Related Work; 3. The ORA-SS Data Model; 4. Using Semantics in Query Processing; 5. Content Search in XML; 6. Keyword Search with Semantics in XML; 7. Conclusion; References; Processing Web Aggregate Queries by Analyzing Search Engine Indices Satoshi Oyama, Taro Tezuka, Hiroaki Ohshima and Katsumi Tanaka; 1. Introduction; 2. A Two-phase Method for Processing Web Aggregate Queries; 2.1. Probe phase; 2.2. Validation phase
327 $a3. Composing Probe and Validation Phases3.1. Access to search engine indices; 3.2. Search with document structures/ linguistic patterns; 3.3. Aggregation; 3.4. Filtering; 4. Web Aggregate Queries; 4.1. Finding typical topics; 4.2. Finding siblings/rivals; 4.3. Finding Landmarks; 5. Conclusion; Acknowledgments; References; Process Mining for Composite Web Services Aiqiang Gao, Dongqing Yang, Shiwei Tang and Yan Fu; 1. Introduction; 2. A Process Model for Composite Web Services; 2.1. Describing Web Services; 2.2. Workflow Graphs; 2.3. A Graph-based Model for Composite Web Services
327 $a3. Supporting Data Structures3.1. Execution Logs; 3.2. Supporting Data Structure; 4. Process Mining Method; 4.1. Main Algorithm; 4.2. Sub-Algorithms Details; 5. Illustration Examples; 6. Related Works; 7. Conclusion; References; Session 1: Semantic Web and Deep Web; Web Resource Categorization for Semantic Web Search M. Pei, K. Nakayama, T. Hara and S. Nishio; 1. Introduction; 2. Categorization Algorithm; 2.1. Approach; 2.2. Process 1: Categorize Offspring; 2.3. Process 2: Extend Category Based on Characteristic Class Name; 2.4. Process 3: Detect Potential Relation from Dictionary
327 $a2.5. Process 4: Detect Relation by Property Pattern Analysis2.6. Flow of Whole Categorization; 3. Experiment for CSWS; 3.1. Data Sources and Evaluations; 3.2. Evaluation Results; 3.3. Comparison with Corese; 4. Conclusions; References; An Effective TOP-K Data Sources Ranking Approach on Deep Web Meifang Li, Guangqi Wang, Derong Shen, Tiezheng Nie, HongKai Zhu and Ge Yu; 1. Introduction; 2. AFP-growth Algorithm; 3. Relevant Attributes Matrix (RAM); 4. Dominance and Relevance based Top-k Style Ranking Algorithm (DR-TRA); 5. Experimental Evaluation; 5.1. Datasets and Setup
327 $a5.2. Performance Comparisons6. Related Work; 7. Conclusions; References; Session 2: Web Service; Automated Web Service Discovery Lev Shulman, Elias Ioup, John Sample, Kevin Shaw and Mahdi Abdelguerfi; 1. Introduction; 2. Background; 2.1. Web Services; 2.2. OGC Geospatial Web Services; 2.3. Previous Work; 3. Web Service Discovery; 4. Validation and Portal Integration; 5. Results; 6. Conclusion; Acknowledgments; References; Visual Media Data Retrieval Based on Web Service Matchmaking Seong-Woo Lee, Chulbum Ahn, Bowon Suh, O-Byoung Kwon and Yunmook Nah; 1. Introduction
327 $a2. Overview of Visual Media Service Architecture
330 $aThe book covers the recent advances in web technologies and applications such as web data management, web information integration, web services, web data warehousing and web data mining, which rapidly changed our life in various ways. Sample Chapter(s)
Chapter 1: Using Semantics in XML Data Management (233 KB)
Contents: