MIT Libraries logoDSpace@MIT

MIT
View Item 
  • DSpace@MIT Home
  • MIT Libraries
  • MIT Theses
  • Graduate Theses
  • View Item
  • DSpace@MIT Home
  • MIT Libraries
  • MIT Theses
  • Graduate Theses
  • View Item
JavaScript is disabled for your browser. Some features of this site may not work without it.

Adaptive consolidation of computational perspectives

Author(s)
Sither, Matthew C. (Matthew Christian)
Thumbnail
DownloadFull printable version (8.750Mb)
Other Contributors
Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science.
Advisor
Patrick H. Winston.
Terms of use
M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission. http://dspace.mit.edu/handle/1721.1/7582
Metadata
Show full item record
Abstract
This thesis describes the design and implementation of machine learning algorithms and real-time recommendations within EWall, a software system used for individual and collaborative information management. In the EWall workspace, users collect and arrange cards, which are compact visual abstractions of information. A significant problem that often arises when humans try to collect information is information overload. Information overload refers to the state of having too much information, and it causes difficulty in discovering relevant information. When affected by information overload, the user loses focus and spends more time filtering out irrelevant information. This thesis first presents a simple solution that uses a set of algorithms that prioritize information. Based on the information the user is working with, the algorithms search for relevant information in a database by analyzing spatial, temporal, and collaborative relationships. A second, more adaptive solution uses agents that observe user behavior and learn to apply the prioritization algorithms more effectively. Adaptive agents help to prevent information overload by removing the burden of search and filter from the user, and they hasten the process of discovering interesting and relevant information.
Description
Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2006.
 
Includes bibliographical references (p. 81).
 
Date issued
2006
URI
http://hdl.handle.net/1721.1/37098
Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Publisher
Massachusetts Institute of Technology
Keywords
Electrical Engineering and Computer Science.

Collections
  • Graduate Theses

Browse

All of DSpaceCommunities & CollectionsBy Issue DateAuthorsTitlesSubjectsThis CollectionBy Issue DateAuthorsTitlesSubjects

My Account

Login

Statistics

OA StatisticsStatistics by CountryStatistics by Department
MIT Libraries
PrivacyPermissionsAccessibilityContact us
MIT
Content created by the MIT Libraries, CC BY-NC unless otherwise noted. Notify us about copyright concerns.