PSM: A New Re-Ranking Algorithm for Named-Page

This year, the IR group of ICT participated in the terabyte track named-page Finding subtask for the first time. Since the document collection is as large as about 426G, our most important goal is to find an efficient way to catch the target web page in such a huge size data set. Meanwhile we want to make the indexing and retrieval processing at a reasonable low cost, both on hardware and time-consuming. We used our “FirteX” engine for indexing and retrieval of this task. The indexing time is within 15 hours and the retrieval time is short enough(less than 2 seconds per query). The main contribution of our work is that we design a Pattern Similarity Matching(PSM) re-ranking algorithm to reorder the results and rank the target document as top 1 as possible. We were glad to see that we’ve got an exciting performance on the last year’s (2005) topics during our experiment. The chief procedure of our work can be divided into three parts as below, which are data preprocess, indexing and retrieval, and re-ranking.