Blogosonomy : Autotagging Any Text Using Bloggers' Knowledge
Shigeru Fujimura, Ko Fujimura, Hidenori Okuda · 2007
There are at least three barriers to utilizing blog tags in classification or navigation: 40% of entries are not (from our observations) tagged, there are many orthographic or synonymous tag variations, and not all tags are informative. We propose a method of multi-autotagging, based on k-NN, which is a case-based classification method. Our method also has the functions of merging tags with the same meaning and identifying informative tags. For realizing these functions, we propose the term weighting method named residual document frequency(RDF); it can score the similarity between tags. Experiments show the effectiveness of our methods. Our autotagging system is generic and can assign tag(s) to any text as well as blog entries although the training data is collected from the blogosophere.