Human Performance on Clustering Web Pages: A Preliminary Study

With the increase in information on the World Wide Web it has become difficult to quickly find desired information without using multiple queries or using a topic-specific search engine. One way to help in the search is by grouping HTML pages together that appear in some way to be related. In order to better understand this task, we performed an initial study of human clustering of web pages, in the hope that it would provide some insight into the difficulty of automating this task. Our results show that subjects did not cluster identically; in fact, on average, any two subjects had little similarity in their web-page clusters. We also found that subjects generally created rather small clusters, and those with access only to URLs created fewer clusters than those with access to the full text of each web page. Generally the overlap of documents between clusters for any given subject increased when given the full text, as did the percentage of documents clustered. When analyzing individ...

• Type: Conference
• Year: 1998
• Where: KDD
• Authors: Sofus A. Macskassy, Arunava Banerjee, Brian D. Davison, Haym Hirsh
• Keywords: Data Mining, KDD 1998, Topic-specific Search Engine, Web Pages, Web-page Clusters