Machine Learning Approach for Homepage Finding Task

This paper describes new machine learning approaches to predict the correct homepage in response to a user's homepage finding query. This involves two phases. In the first phase, a decision tree is generated to predict whether a URL is a homepage URL or not. The decision tree then is used to filter out non-homepages from the webpages returned by a standard vector space IR system. In the second phase, a logistic regression analysis is used to combine multiple sources of evidence on the remaining webpages to predict which homepage is most relevant to a user's query. 100 queries are used to train the logistic regression model and another 145 testing queries are used to evaluate the model derived. Our results show that about 84% of the testing queries had the correct homepage returned within the top 10 pages. This shows that our machine learning approaches are effective since without any machine learning approaches, only 59% of the testing queries had their correct answers retur...

• Type: Conference
• Year: 2001
• Where: TREC
• Authors: Wensi Xi, Edward A. Fox
• Keywords: Correct Homepage, Machine Learning Approaches, Testing Queries, TREC 2001, TREC 2008