Learn from web search logs to organize search results (2007)
| Venue: | In SIGIR |
| Citations: | 25 - 4 self |
BibTeX
@INPROCEEDINGS{Wang07learnfrom,
author = {Xuanhui Wang},
title = {Learn from web search logs to organize search results},
booktitle = {In SIGIR},
year = {2007},
pages = {87--94}
}
OpenURL
Abstract
Effective organization of search results is critical for improving the utility of any search engine. Clustering search results is an effective way to organize search results, which allows a user to navigate into relevant documents quickly. However, two deficiencies of this approach make it not always work well: (1) the clusters discovered do not necessarily correspond to the interesting aspects of a topic from the user’s perspective; and (2) the cluster labels generated are not informative enough to allow a user to identify the right cluster. In this paper, we propose to address these two deficiencies by (1) learning “interesting aspects ” of a topic from Web search logs and organizing search results accordingly; and (2) generating more meaningful cluster labels using past query words entered by users. We evaluate our proposed method on a commercial search engine log data. Compared with the traditional methods of clustering search results, our method can give better result organization and more meaningful labels.







