Learning Semantic Categories from Clickthrough Logs

Mamoru Komachi, Shimpei Makimoto, Kei Uchiumi, Manabu Sassano

Abstract: As the web grows larger, knowledge acquisition from the web has gained increasing attention. In this paper, we propose using web search clickthrough logs to learn semantic categories. Experimental results show that the proposed method greatly outperforms previous work using only web search query logs.