WIM at TREC 2007

This paper introduced the four tracks that WIM-Lab Fudan University had taken part in at TREC 2007. For spam track, a multi-centre model was proposed considering the characteristics of spam mails in contrast of traditional 2-class classification methodology, and the incremental clustering and closeness-based classification methods were applied this year. For enterprise track, our research was mainly focused on ranking functions of experts and selecting correct supporting documents regarding to a given topic. For legal track, the effects of word distribution model in query expansion and various corpus pre-processing methods were mainly evaluated. For genomics track, three score methods were proposed to find the most relevant text snippets to a given topic. This paper gives an overview of the methods employed for each sub tasks, and compares the results of each track.