Context-Aware Online Commercial Intention Detection

With more and more commercial activities moving onto the Internet, people tend to purchase what they need through Internet or conduct some online research before the actual transactions happen. For many Web users, their online commercial activities start from submitting a search query to search engines. Just like the common Web search queries, the queries with commercial intention are usually very short. Recognizing the queries with commercial intention against the common queries will help search engines provide proper search results and advertisements, help Web users obtain the right information they desire and help the advertisers benefit from the potential transactions. However, the intentions behind a query vary a lot for users with different background and interest. The intentions can even be different for the same user, when the query is issued in different contexts. In this paper, we present a new algorithm framework based on skip-chain conditional random field (SCCRF) for ...

• Type: Conference
• Year: 2009
• Where: ACML
• Authors: Derek Hao Hu, Dou Shen, Jian-Tao Sun, Qiang Yang, Zheng Chen
• Keywords: ACML 2009, Commercial Activities, Commercial Intention, Machine Learning, Search Engine