Mining, Modeling, and Recommending 'Things' in Social Media (eBook, PDF)

4th International Workshops, MUSE 2013, Prague, Czech Republic, September 23, 2013, and MSM 2013, Paris, France, May 1, 2013, Revised Selected Papers
Redaktion: Atzmueller, Martin; Trattner, Christoph; Scholz, Christoph; Chin, Alvin

• Format: PDF

Produktbeschreibung

This book constitutes the thoroughly refereed joint post-workshop proceedings of the 4th International Workshop on Mining Ubiquitous and Social Environments, MUSE 2013, held in Prague, Czech Republic, in September 2013, and the 4th International Workshop on Modeling Social Media, MSM 2013, held in Paris, France, in May 2013. The 8 full papers included in the book are revised and significantly extended versions of papers submitted to the workshops. The focus is on collective intelligence in ubiquitous and social environments. Issues tackled include personalization in social streams, recommendations exploiting social and ubiquitous data, and efficient information processing in social systems. Furthermore, this book presents work dealing with the problem of mining patterns from ubiquitous social data, including mobility mining and exploratory methods for ubiquitous data analysis.

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Produktdetails

• Verlag: Springer Nature Switzerland
• Seitenzahl: 151
• Erscheinungstermin: 24. Dezember 2014
• Englisch
• ISBN-13: 9783319147239
• Artikelnr.: 43789688

Inhaltsangabe

Exploratory Subgroup Analytics on Ubiquitous Data.- Personalized Network Activity Feeds: Finding Needles in Haystacks.- Ontology-Enabled Access Control and Privacy Recommendations.- Refining Frequency-Based Tag Reuse Predictions by Means of Time and Semantic Context.- Forgetting the Words but Remembering the Meaning: Modeling Forgetting in a Verbal and Semantic Tag Recommender.- Utilizing Online Social Network and Location-Based Data to Recommend Products and Categories in Online Marketplaces.- Open Smartphone Data for Structured Mobility and Utilization Analysis in Ubiquitous Systems.- Predictability Analysis of Aperiodic and Periodic Model for Long-Term Human Mobility Using Ambient Sensors.