近年來有越來越多的使用者在網路上擁有自已的部落格。每位使用者在部落格中都有極大的自由去決定部落格的形式及文章的分類，這樣的自由也造成了分類不一致的現象。
為解決這樣的問題，本篇論文討論了許多現行方法，最後決定藉著
Ontology 的特性，找出內容相似的記事分類，以建立出一個專屬於
每一位使用者的記事分類推薦系統。
就目前所知，以往使用 Ontology 來比較語意上的相近(semantic
similarity)，只能同時比較兩個詞(term / node)的相近程度。但在
這篇論文中，我們發展出新方法可以同時比較兩個群體的詞在
Ontology 中的語意相近程度。我們使用蕃薯藤的部落格來當作實驗
的主體，根據實驗結果顯示，這兩種方法不但可行而且成效顯著。

This paper proposes a framework to automatically map user-defined categories in blog. The proposed
framework is composed of a series of procedures including information extraction from
blog, building the personal ontology, and comparing semantic similarities between user-defined
categories. Our novel semantic similarity techniques can determine how similar two sets of information
concepts are, based on a given ontology. The experimental results demonstrated that
our framework and our proposed semantic similarity techniques are effective.

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