Summer 2008

TREC 2008 Relevance Feedback Track. The purpose of this track is to "provide a framework for exploring the effects of different factors on the success of relevance feedback". The data set provided for this task was GOV2, a partial crawl of the web representing the US government. This data set contains over 25 million documents and takes up nearly half of a terabyte of space. We used a Java indexing tool Lucene to index the documents. Using this index we were able to run queries, and pick the best ones for the task at hand. We then used a topic model developed by Ha Thuc Viet to use the relevance feedback information for quiery improvement.

Last Updated 08|09|2008