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Titlebook: Recommendation and Search in Social Networks; Özgür Ulusoy,Abdullah Uz Tansel,Erol Arkun Book 2015 Springer International Publishing Switz

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Book 2015broader 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 th
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Comparison of Emoticon Recommendation Methods to Improve Computer-Mediated Communication,t emoticon selection. We also integrated the proposed and baseline systems, leading to a performance improvement of approximately 73.0 % in the same experiment. Evaluation of respondents’ perceptions of the three systems utilizing an SD scale and factor analysis is also described in this paper.
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An Improved Collaborative Recommendation System by Integration of Social Tagging Data, relationships such as friendship and membership, in measuring the closeness of two users. Then we define a new item prediction method which makes use of both user-to-user similarity and item-to-item similarity. Experimental outcomes on Last.fm data produce the positive results that show the accuracy of our proposed approach.
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2190-5428 in networks.Gives methods on improving computer-mediated co.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 su
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Comparison of Emoticon Recommendation Methods to Improve Computer-Mediated Communication,novative emoticon database consisting of a table of emoticons with points expressed from each of 10 distinctive emotions was created. An evaluation experiment showed that our proposed system achieved an improvement of 28.1 points over a baseline system, which recommends emoticons based on users’ pas
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Accuracy Versus Novelty and Diversity in Recommender Systems: A Nonuniform Random Walk Approach,ust information may be processed in a number of ways, including the random walks in the social graph, where every step in the walk is chosen almost uniformly at random from the available choices. Although this strategy yields satisfactory results in terms of the novelty and the diversity of the prod
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Social Network Derived Credibility, a variety of indicators (e.g., explicit ratings, profile information, etc.). Through human-subject experimentation with an online social network-style platform, we focus on the determination of credibility in ego-centric networks, where participants are able to observe salient social network proper
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