The massive growth in size of the Internet has resulted in increased difficulty in organizing and searching through the information present on it. Several strategies have been employed to tackle this problem. With the coming of Web2.0, user-created data and sharing of information among peers, folksonomy has become the norm for categorization of data. The loose structure of folksonomy has led to easier categorization of the huge amounts of information but has also given rise to some serious problems. Users tag information based on their own experiences, preferences and common sense. This leads to difficulties in searching and organization of information. In this work, we describe that since user common sense has generated both folksonomy and a corpus of machine common sense, it seems appropriate that the common sense be used for addressing the problem of search in folksonomy. An architecture for such an operation will be created which allows the application of machine common sense and user personalization to address the issues of search in folksonomy-based systems.

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