Browsing System for Weblog Articles based on Automated Folksonomy

Folksonomy is a new manual classification scheme based on tagging efforts of users with freely chosen keywords. In folksonomy, a user puts an item (i.e. a photo, a book mark) on a server and shares it with other users. The owner and even the other users can attach tags to this item for their own classification, and they reflect many one’s viewpoints. Since tags are chosen from users’ vocabulary and contain many one’s viewpoints, classification results are easy to understand for ordinary users. As a result, folksonomy serves as an efficient browsing method, because users can grasp the essence of items by looking at the tags. Even though the scalability of folksonomy is much higher than the other manual classification schemes, the method cannot deal with tremendous number of items such as whole weblog articles on the Internet. For the purpose of solving this problem, we try to automate folksonomy to enhance weblog browsing. We create a “tagger” which is a program to determine whether a particular tag should be attached to an item. In addition, we propose a method to create a candidate tag set, which is a list of tags that may be attached to items, from weblog category names. We achieved around 95% precision compared to a candidate tag set created manually.