Search (3 results, page 1 of 1)

  • × author_ss:"Watters, C."
  • × theme_ss:"Internet"
  • × year_i:[2000 TO 2010}
  1. Kellar, M.; Watters, C.; Shepherd, M.: ¬A field study characterizing Web-based information seeking tasks (2007) 0.00 
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    Abstract
    Previous studies have examined various aspects of user behavior on the Web, including general information-seeking patterns, search engine use, and revisitation habits. Little research has been conducted to study how users navigate and interact with their Web browser across different information-seeking tasks. We have conducted a field study of 21 participants, in which we logged detailed Web usage and asked participants to provide task categorizations of their Web usage based on the following categories: Fact Finding, Information Gathering, Browsing, and Transactions. We used implicit measures logged during each task session to provide usage measures such as dwell time, number of pages viewed, and the use of specific browser navigation mechanisms. We also report on differences in how participants interacted with their Web browser across the range of information-seeking tasks. Within each type of task, we found several distinguishing characteristics. In particular, Information Gathering tasks were the most complex; participants spent more time completing this task, viewed more pages, and used the Web browser functions most heavily during this task. The results of this analysis have been used to provide implications for future support of information seeking on the Web as well as direction for future research in this area.
  2. Watters, C.; Wang, H.: Rating new documents for similarity (2000) 0.00 
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    Abstract
    Electronic news has long held the promise of personalized and dynamic delivery of current event new items, particularly for Web users. Although wlwctronic versions of print news are now widely available, the personalization of that delivery has not yet been accomplished. In this paper, we present a methodology of associating news documents based on the extraction of feature phrases, where feature phrases identify dates, locations, people and organizations. A news representation is created from these feature phrases to define news objects that can then be compared and ranked to find related news items. Unlike tradtional information retrieval, we are much more interested in precision than recall. That is, the user would like to see one or more specifically related articles, rather than all somewhat related articles. The algorithm is designed to work interactively the the user using regular web browsers as the interface
  3. Shepherd, M.; Duffy, J.F.J.; Watters, C.; Gugle, N.: ¬The role of user profiles for news filtering (2001) 0.00 
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    Date
    29. 9.2001 13:59:13

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