Common Sense and Folksonomy

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

Klappentext
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.