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  1. Proceedings of the 2012 workshop on Data-driven user behavioral modelling and mining from social media (DUBMMSM '12)
  2. Ranking and combining social network data for web personalization
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Analyzing social media friendship for personalization
Ranking and combining social network data for web personalization
Identifying and characterizing user communities on Twitter during crisis events
Twitter user behavior understanding with mood transition prediction
A collective synchronous behavior model on social media
Please spread: recommending tweets for retweeting with implicit feedback
Using social data for resume job matching
Analyzing sentiments from street harassment stories
Probabilistic macro behavioral targeting
Modeling online collective emotions
Pinteresting: towards a better understanding of user interests
The framework of a people recommender based on a time series of user preferences

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Ranking and combining social network data for web personalization

Content Provider ACM Digital Library
Author Hao, Hongwei Zhong, Ning Zeng, Yi Ren, Xu Wang, Yan
Abstract Various Web-based social network data reflect user interests from multiple perspectives in a distributed environment. They need to be integrated for better user modelling and personalized services. We argue that in different scenarios, different social networks play different roles and their degrees of importance are not equivalent. Hence, ranking strategies among different social network data sources are needed. In addition, combining different social network data can produce interesting subsets of these data with different levels of importance. In this paper, we propose social network data ranking and composition strategies, we validate the proposed methods by collaboration network data (Semantic Web Dog Food) and micro-blogging data (from Twitter), then we use the ranked and composed results for developing a Web-based personalized academic visit recommendation system to show their potential effectiveness.
Starting Page 15
Ending Page 18
Page Count 4
File Format PDF
ISBN 9781450317078
DOI 10.1145/2390131.2390139
Language English
Publisher Association for Computing Machinery (ACM)
Publisher Date 2012-10-29
Publisher Place New York
Access Restriction Subscribed
Subject Keyword Web personalization Interest analysis Social networks
Content Type Text
Resource Type Article
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