Fujitsu Laboratories Trec7 Report 2 System Description 2.1 Overall 2.2 the Search System Tera

In our rst participation in TREC, our focus was on improving the basic ranking systems and applying text clustering techniques for query expansion. We tested a variety of techiniques including reference measures, passage retrieval, and data fusion for the basic ranking systems. Some techiniques were used in the o cial run, others were not used because of time limitations. We applied the text clustering techiniques for query expansion with a text clustering engine. Clustering base query expansion uses the top N best text clusters from the top 1000 documents instead of just using the top N documents. Clustering base query expansion produces better results than simple query expansion based on passage retrieval. We submitted three runs, Flab7at , Flab7ad, and Flab7atE. Flab7at is combination of ranking and query expansion by clustering the top 1000 documents on the title eld, Flab7ad is combination of ranking and query expansion by clustering on the description eld, and Flab7atE is combination of ranking with Boolean (existence) operators and query expansion by passage retrieval.