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The increasing volume of information about goods and services has been growing confusion for online buyers in cyberspace and this problem still continues. One of the most important ways to deal with the information overload is using a system called recommender system. The task of a recommender system is to offer the most appropriate and the nearest product to the user's demands and needs. In this...
The study of social networks has gained much interest from the research community in recent years. Most of the existing algorithms proposed for communities determination are based on the topological features of social networks. In this paper, we propose a new objective function where we incorporate the value of structure, semantic similarity, a bees colonies algorithm to optimize our objective function...
Studies have found that more and more diseases have some regional characteristics because of the effects of several factors such as people's living habits and nature environment. Concerning that these regional diseases haven't received enough attention at the initial stage of their discoveries, and the limitations of lack of research data about regional diseases shall be remedied. The paper intends...
In our prior work, we identified rules for use in recommendation algorithms on Online Social Network (OSN) in order to increase the relevance of content suggested to a user. The resulting recommendation algorithms filter out and prioritize event types for OSN users (such as photo posts by friends, status posts, shared content, etc.), and are thereby intended to reduce information overload. This paper...
Organizations measure their social audience based on the number of users, fans, and followers on social media. Every social media platform has its user identity and a single user is present across varied platforms. Due to the disconnected user profiles, identifying duplicate users across media is non-trivial. There is a need to create a complete view of a user for various applications such as targeting...
One highly studied aspect of social networks is the identification of influential nodes that can spread ideas in a highly efficient way. The vast majority of works in this field have investigated the problem of identifying a set of nodes, that if "seeded" simultaneously, would maximize the information spread in the network. Yet, the timing aspect, namely, finding not only which nodes should...
The problem of community detection in social media has been widely studied in the social networking community in the context of the structure of the underlying graphs. Most community detection algorithms use the links between the nodes in order to determine the dense regions in the graph. These dense regions are the communities of social media in the graph. Such methods are typically based purely...
When monitoring blog articles for the tracking of a certain personality or product, the automatic identification of topic clusters is of high interest. Clustering by textual content is a popular method to accomplish this. In this paper we investigate how links between individual blog articles can be used to support this clustering with another dimension of information. Given the existing component...
Similarity breeds connections, the principle of homophily, has been well studied in existing sociology literature. Several studies have observed this phenomenon by conducting surveys on human subjects. These studies have concluded that new ties are formed between similar individuals. This phenomenon has been used to explain several socio-psychological concepts such as segregation, community development,...
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