著者

松尾 豊 福田 隼人 石塚 満

出版者

一般社団法人 人工知能学会

雑誌

人工知能学会論文誌 (ISSN:13460714)

巻号頁・発行日

vol.18, no.4, pp.203-211, 2003 (Released:2003-05-20)

参考文献数

14

被引用文献数

1 1 5

---

We develop a browsing support system which learns user's interests and highlights keywords based on a user's browsing history. Monitoring the user's access to the Web enables us to detect ``familiar words'' for the user. We extract keywords at the current page, which are relevant to the familiar words, and highlight them. The relevancy is measured by the biases of co-occurrence, called IRM (Interest Relevance Measure). Our system consists of three components; a proxy server which monitors access to the Web, a frequency server which stores frequency of words in the accessed Web pages, and a keyword extraction module. We show the effectiveness of our system by experiments.