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Titlebook: Computational Social Networks; 4th International Co My T. Thai,Nam P. Nguyen,Huawei Shen Conference proceedings 2015 Springer International

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Johanna T. Dwyer,Adam Drewnowski a limited budget such that the result of the survey is biased to the minority opinions. This approach has a wide range of potential applications, e.g. collecting complaints from the customers of a new product while most of them are satisfied. We formally define the problem of computing such group w
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Karisma Karisma,Pardis Moslemzadeh Tehranication (LOC), Organization (ORG) and so on. There have been many approaches proposed to tackle this problem in both formal texts such as news or authorized web content and short texts such as contents in online social network. However, those texts were written in languages other than Vietnamese. In
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0302-9743 selected from 101 submissions and cover topics on social information diffusion; network clustering and community structure; social link prediction and recommendation; and social network structure analysis..978-3-319-21785-7978-3-319-21786-4Series ISSN 0302-9743 Series E-ISSN 1611-3349
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Micronutrient Status in Affluent Societieshe target region is used to reduce the range of candidate POIs. At last, the proposed method ranks the candidate POIs to meet the user’s personalized need by combining the user preference, attraction of a POI on the target user, and social recommendations from friends. Experimental results show that the proposed method is feasible and effective.
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Food Insecurity and Poverty in Germanyser social relationship, check-in distance and check-in type as three key features. Secondly, we take the prediction problem as a classification problem and choose SVM (support vector machine) to classify it. At last some experiment results show our algorithm valid to some extent.
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A Point-of-Interest Recommendation Method Based on User Check-in Behaviors in Online Social Networkhe target region is used to reduce the range of candidate POIs. At last, the proposed method ranks the candidate POIs to meet the user’s personalized need by combining the user preference, attraction of a POI on the target user, and social recommendations from friends. Experimental results show that the proposed method is feasible and effective.
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