Recognition and representation of user interest

With the growth of the internet and other media of communication, locating information on the topic of interest is less a problem of finding related documents than determining which particular documents are valuable. Often, the desired information is obscured within a long list of resources. Users b...

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Bibliographic Details
Main Author: Badi, Rajiv Ravindranath
Other Authors: Shipman, Frank
Format: Others
Language:en_US
Published: Texas A&M University 2007
Subjects:
Online Access:http://hdl.handle.net/1969.1/4997
Description
Summary:With the growth of the internet and other media of communication, locating information on the topic of interest is less a problem of finding related documents than determining which particular documents are valuable. Often, the desired information is obscured within a long list of resources. Users become inundated with so much information that the task of sifting through it takes the majority of time on a given information task. Users look at multiple documents at once to find answers to their questions, and switch between documents to get the “complete” picture. New systems are needed that help users cull through related documents to gain the information they need. As a part of the Document Triage Project, we have been looking at ways to help users in sifting through information. The Document Triage Project is developing tools to recognize, represent, communicate, and visualize user interest across applications. The topic of this thesis is recognizing user interest and providing an infrastructure to represent that interest so that it can be shared across the software applications involved in triage. Based on this inferred interest, applications can help users in their triage task by providing visualizations or other functionality. The applications could involve one or many reading interfaces (e.g., a browser, or an editor), an information organizing system (e.g., Visual Knowledge Builder) and search interfaces (the application providing the document collection; e.g., a search engine). To recognize user interest, data is gathered from the user’s reading, navigational and interpretive activities. Algorithms based on statistical models and qualitative analyses of user behavior in triage are used to infer interest. A light-weight infrastructure called Interest Profile Manager has been developed for the representation of interest values and the corresponding metadata. Interest Profile Manager also provides text processing capability, interest analysis functionality, sharing of data across applications and event propagation.