| 英文摘要 | With the rapid development of the World Wide Web, social tagging systems are becoming more and more popular, such as Delicious, Flickr, Douban, last.fm, citeulike, and so on, which provide functions including storage, sharing, social tagging, reviewing, rating, and constructing user communities. Tagging systems allow users to save resources (i.e. web pages, photos, books, movies, music, science-related content, etc.) into web sites, and choose keywords as tags freely. During the interaction process between users and systems, a large number of user-generated data are available, which show users’ interests and represent their summarization for the semantic information in the resources. The user behavior data reflect their subjective cognitive characteristics and relevant knowledge structure, and present social collaborative characteristics. Therefore, how to utilize such data to provide services for users becomes the focus of attention by the academia and business world. Social tagging systems involve many elements such as resources, users, tags, reviews, ratings, and so on. How to integrate all these elements to deepen the understanding of social tagging systems, how to help users deal with the tag redundancy and semantic ambiguity problem, and how to efficiently browse and search their resources are essential tasks. The main work and contributions of the thesis are summarized as follows. 1. The information integration mechanism of social tagging systems is studied from a holism and complexity perspective. The needs of users are described by applying the Maslow’s hierarchy of needs theory, then multiple spaces are used to reflect elements in social tagging systems, such as resources, users, tags, reviews, rating, knowledge, and so on. The purpose is to help users achieve the cognitive emergence process from data, information to knowledge and intelligence through the integration and interaction among different spaces in tagging systems. Based on such analysis, we propose the idea of a user-system-cooperated user-centered systematic design and its computation for better satisfying the needs of users. 2. To deal with the problems of tag redundancy and semantic ambiguity , a semantic related tag mining approach based on non-negative matrix factorization method is proposed. We define relational sets between resources and tags to discover the latent semantic relevance among tags in the tag space from a perspective of the relationship between users' resour... |
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