Recommendation and Search in Social Networks (eBook, PDF)

Redaktion: Ulusoy, Özgür; Arkun, Erol; Tansel, Abdullah Uz

• Format: PDF

Produktbeschreibung

This edited volume offers a clear in-depth overview of research covering a variety of issues in social search and recommendation systems. Within the broader context of social network analysis it focuses on important and up-coming topics such as real-time event data collection, frequent-sharing pattern mining, improvement of computer-mediated communication, social tagging information, search system personalization, new detection mechanisms for the identification of online user groups, and many more. The twelve contributed chapters are extended versions of conference papers as well as completely new invited chapters in the field of social search and recommendation systems. This first-of-its kind survey of current methods will be of interest to researchers from both academia and industry working in the field of social networks.

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Produktdetails

• Verlag: Springer Nature Switzerland
• Seitenzahl: 289
• Erscheinungstermin: 12. Februar 2015
• Englisch
• ISBN-13: 9783319143798
• Artikelnr.: 43783769

Inhaltsangabe

Adaptive Identification of Hashtags for Real-Time Event Data Collection.- Comparison of Emoticon Recommendation Methods to Improve Computer-Mediated Communication.- Accuracy vs Novelty & Diversity in Recommender Systems: A Non-Uniform Random Walk Approach.- Social Network Derived Credibility.- Anonymizing Social Network Data for Maximal Frequent-Sharing Pattern Mining.- A Comprehensive Analysis of Detection of Online Paid Posters.- An Improved Collaborative Recommendation System by Integration of Social Tagging Data.- Personalization of Web Search using Social Signals.- The Pareto Principle is Everywhere: Finding Informative Sentences for Opinion Summarization through Leader Detection.- Social Media Question Asking: A Developing Country Perspective.- Evolutionary Influence Maximization in Viral-Marketing.- Mining and Analyzing the Italian Parliament: Party Structure and Evolution.