E-Commerce, and Web Technologies (eBook, PDF)

14th International Conference, EC-Web 2013, Prague, Czech Republic, August 27-28, 2013, Proceedings
Redaktion: Huemer, Christian; Lops, Pasquale

• Format: PDF

Produktbeschreibung

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.

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Produktdetails

• Verlag: Springer Berlin Heidelberg
• Seitenzahl: 211
• Erscheinungstermin: 23. August 2013
• Englisch
• ISBN-13: 9783642398780
• Artikelnr.: 44129511

Inhaltsangabe

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.