This book constitutes the refereed proceedings of the 14th International Conference on Electronic Commerce and Web Technologies (EC-Web) held in Prague, Czech Republic, in August 2013. In 2013, EC-Web focused on recommender systems, semantic e-business, business services and process management, and agent-based e-commerce. The 13 full and 6 short papers accepted for EC-Web, selected from 43 submissions, were carefully reviewed based on their originality, quality, relevance, and presentation.
This book constitutes the refereed proceedings of the 14th International Conference on Electronic Commerce and Web Technologies (EC-Web) held in Prague, Czech Republic, in August 2013. In 2013, EC-Web focused on recommender systems, semantic e-business, business services and process management, and agent-based e-commerce. The 13 full and 6 short papers accepted for EC-Web, selected from 43 submissions, were carefully reviewed based on their originality, quality, relevance, and presentation.
Produktdetails
Produktdetails
Lecture Notes in Business Information Processing 152
Session 1: Opening. BRF: A Framework of Retrieving Brand Names of Products in Auction Sites. An Adaptive Social Influence Propagation Model Based on Local Network Topology. Session 2: Semantics and Agents. A Rule Based Personalized Location Information System for the Semantic Web. DIESECT: A Distributed Environment for Simulating E commerce Contracts. Semi automated Structural Adaptation of Advanced E Commerce Ontologies. Session 3: Business Processes. SDRule L: Managing Semantically Rich Business Decision Processes. A Hybrid Approach for Business Environment Aware Management of Service Based Business Processes. Discovering Workflow Aware Virtual Knowledge Flows for Knowledge Dissemination. Session 4: Recommender I. An Emotion Dimensional Model Based on Social Tags: Crossing Folksonomies and Enhancing Recommendations. Cold Start Management with Cross Domain Collaborative Filtering and Tags. UtilSim: Iteratively Helping Users Discover Their Preferences. Session 5: Recommender II. Contextual eVSM: A Content Based Context Aware Recommendation Framework Based on Distributional Semantics. Context Aware Movie Recommendations: An Empirical Comparison of Pre filtering, Post filtering and Contextual Modeling Approaches. Matching Ads in a Collaborative Advertising System. Session 6: Recommender III. Confidence on Collaborative Filtering and Trust Based Recommendations. Smoothly Extending e Tourism Services with Personalized Recommendations: A Case Study. Exploiting Big Data for Enhanced Representations in Content Based Recommender Systems. Recommendations Based on Different Aspects of Influences in Social Media. Robustness Analysis of Naive Bayesian Classifier Based Collaborative Filtering.
Session 1: Opening. BRF: A Framework of Retrieving Brand Names of Products in Auction Sites. An Adaptive Social Influence Propagation Model Based on Local Network Topology. Session 2: Semantics and Agents. A Rule Based Personalized Location Information System for the Semantic Web. DIESECT: A Distributed Environment for Simulating E commerce Contracts. Semi automated Structural Adaptation of Advanced E Commerce Ontologies. Session 3: Business Processes. SDRule L: Managing Semantically Rich Business Decision Processes. A Hybrid Approach for Business Environment Aware Management of Service Based Business Processes. Discovering Workflow Aware Virtual Knowledge Flows for Knowledge Dissemination. Session 4: Recommender I. An Emotion Dimensional Model Based on Social Tags: Crossing Folksonomies and Enhancing Recommendations. Cold Start Management with Cross Domain Collaborative Filtering and Tags. UtilSim: Iteratively Helping Users Discover Their Preferences. Session 5: Recommender II. Contextual eVSM: A Content Based Context Aware Recommendation Framework Based on Distributional Semantics. Context Aware Movie Recommendations: An Empirical Comparison of Pre filtering, Post filtering and Contextual Modeling Approaches. Matching Ads in a Collaborative Advertising System. Session 6: Recommender III. Confidence on Collaborative Filtering and Trust Based Recommendations. Smoothly Extending e Tourism Services with Personalized Recommendations: A Case Study. Exploiting Big Data for Enhanced Representations in Content Based Recommender Systems. Recommendations Based on Different Aspects of Influences in Social Media. Robustness Analysis of Naive Bayesian Classifier Based Collaborative Filtering.
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