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Topic detection and tracking (TDT) under modern media circumstances has been dramatically innovated with the ever-changing social network and inconspicuous connections among participants in the internet communities. Apart from the inherent word features of analysing materials, such as news articles and personal or professional comments, incidental information attracts increasing attention from the...
With the rapid development of the Internet, more and more people use social networks to share information and express their views, which lead to a vigorous growth of information. How to select useful and interesting information for users, that is user topic interest, gets more and more attention. Tag functionality in microblog can get user topic interests easily and achieve information recommendation...
Topic detection always plays an important role in social network analysis. In this paper, we focus on a very simple question that how to choose the terms that can represent a topic better before topic detection. To tackle this problem, we propose an effective model named Topic Model based on Entropy and LDA (TMELDA). The model is built on the user intention, which means different users have different...
Users can annotate themselves using free tags in micro-blogging website such as Sina Weibo. The tags of a user demonstrate the characteristics of the user and are generally in a random order without any importance or relevance information. It limits the effectiveness of user tags in system recommendation and other applications. In this paper, we proposed a user tag ranking schema which is based on...
Online social networks such as Sina Weibo micro-blogging website allow user to annotate himself (or herself) using tags, which describe the characteristics of the user. Many researches have been done on photos, films, commodities but rare researches on users. In this paper, we try to recommend tags for users who can communicate directly with other users. Our method is based on interactive relations...
The hidden knowledge in the information network has attracted a large number of researchers from different subjects such as sociology, physics and computer science. Community discovery has great significance for the analysis of information network structure, the understanding of its function, the discovery of its hidden patterns, and the predication of its behavior. In the practical life, people tend...
The hidden knowledge in the information network has attracted a large number of researchers from different subjects such as sociology, physics and computer science. Community discovery has great significance for the analysis of information network structure, the understanding of its function, the discovery of its hidden patterns, and the predication of its behavior. In the practical life, people tend...
Recently, as more and more social network data has been published in one way or another, preserving privacy in publishing social network data becomes an important concern. With some local knowledge about individuals in a social network, an adversary may attack the privacy of some victims easily. Unfortunately, most of the previous studies on privacy preservation can deal with relational data only,...
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