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In a disaster, accurate information is a resource that is often in short supply. The combination of rapidly unfolding events and the frequent loss of communication infrastructure including mobile phones, landlines, Internet and television broadcast make it difficult to gain situational awareness. And while there is obvious value in aggregating information for centralized emergency authorities, disasters...
Collaborative filtering (CF) based recommender systems have gained wide popularity in Internet companies like Amazon, Netflix, Google News, and others. These systems make automatic predictions about the interests of a user by inferring from information about like-minded users. Realtime CF on highly sparse massive datasets, while achieving a high prediction accuracy, is a computationally challenging...
In this paper, Singular Value Decomposition (SVD) is combined with hybrid collaborative filtering (CF), proved to be an effective solution for sparsity problem. SVD is utilized in order to reduce the dimension of the user-pageview matrix obtained from web usage mining. Afterwards, both low-rank matrices are employed in order to generate item-based and user-based predictions. A framework for building...
During the last few years, the search result clustering has attracted a substantial amount of research. In this paper, we present a comparative study of the performance of fuzzy clustering algorithms, namely Fuzzy C-Means (FCM), and Gustafson-Kessel (GK) algorithms with clustering search results. Therefore, there is a need to reduce the information, help filtering out irrelevant items, and favors...
Clustering techniques have been used by many intelligent software agents in order to retrieve, filter, and categorize documents available on the World Wide Web. Clustering is also useful in extracting salient features of related Web documents to automatically formulate queries and search for other similar documents on the Web. Traditional clustering algorithms either use a priori knowledge of document...
Recommender systems help to overcome the problem of information overload on the Internet by providing personalized recommendations to the users. Content-based filtering and collaborative filtering are usually applied to predict these recommendations. Among these two, Collaborative filtering is the most common approach for designing e-commerce recommender systems. Two major challenges for CF based...
The rapid development of blogs has brought on some serious problems such as disclosure of sensitive information, spread of unhealthy information, etc. So it is very important for supervisors to detect them. The common methods based on search engines have some drawbacks such as lower efficiency and lower precision because they need to retrieve and update blog pages frequently, and to analyze all blog...
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