Metadata
Title
Separating the Swarm: Categorization Methods for User Sessions on the Web
Category
general
UUID
5fba57faff1c461e94ee426522ac6c19
Source URL
https://idl.uw.edu/papers/separating-the-swarm
Parent URL
https://idl.uw.edu/papers
Crawl Time
2026-03-11T02:54:40+00:00
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Separating the Swarm: Categorization Methods for User Sessions on the Web

Source: https://idl.uw.edu/papers/separating-the-swarm Parent: https://idl.uw.edu/papers

Jeffrey Heer, Ed H. Chi. Proc. ACM Human Factors in Computing Systems (CHI), 2002

Jeffrey Heer, Ed H. Chi

Proc. ACM Human Factors in Computing Systems (CHI), 2002

Materials

PDF

Abstract

Understanding user behaviors on Web sites enables site owners to make sites more usable, ultimately helping users to achieve their goals more quickly. Accordingly, researchers have devised methods for categorizing user sessions in hopes of revealing user interests. These techniques build user profiles by combining users’ navigation paths with other data features, such as page viewing time, hyperlink structure, and page content. Previously, we have presented complex techniques of combining many of these data features to cluster user profiles. In this paper, we introduce a user study and a systematic evaluation of these different data features and their associated weighting schemes. We present the results of our study, including accuracy measures for a number of clustering approaches, and offer recommendations for Web analysts. While further investigation over more sites is needed to definitively settle on a robust scheme, we have characterized this analytic space.

BibTeX

@inproceedings{2002-separating-the-swarm,
  title = {Separating the Swarm: Categorization Methods for User Sessions on the Web},
  author = {Heer, Jeffrey AND Chi, Ed},
  booktitle = {Proc. ACM Human Factors in Computing Systems (CHI)},
  year = {2002},
  pages = {243--250},
  url = {https://idl.uw.edu/papers/separating-the-swarm},
  doi = {10.1145/503376.503420}
}

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