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Knowledge trading : computational support for individual and collaborative sense-making activities

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dc.contributor.advisor William L. Porter. en_US
dc.contributor.author Keel, Paul E. (Paul Erich) en_US
dc.contributor.other Massachusetts Institute of Technology. Dept. of Architecture. en_US
dc.date.accessioned 2005-09-27T18:27:19Z
dc.date.available 2005-09-27T18:27:19Z
dc.date.copyright 2004 en_US
dc.date.issued 2004 en_US
dc.identifier.uri http://hdl.handle.net/1721.1/28807
dc.description Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Architecture, 2004. en_US
dc.description Includes bibliographical references (leaves 127-132). en_US
dc.description.abstract (cont.) outlined. 2. Demonstration that computer systems can use the discovered relations among data items to help users search for relevant information, prioritize the data exchange between collaborating users, and visualize data in various ways. This investigation looks at how a human's increasing knowledge about a problem space is influential in the subsequent accumulation of new data. The findings are converted into computational equivalents that can support individual and collaborative sense-making processes. en_US
dc.description.abstract This dissertation explores the potential for computational systems to analyze and support individual and collaborative human sense-making activities. In this context human sense-making refers to the act of mentally and physically relating pieces of information so as to develop an understanding of a particular situation. Human sense-making activities such as brainstorming, decision-making, and problem solving sessions often produce a lot of data such as notes, sketches, and documents. The participants of sense-making activities usually develop a good understanding of the relations among these individual data items. These relations define the context. Because the relations remain within the minds of the participants they are neither accessible to outsiders and computational systems nor can they be recorded or backed up. This dissertation outlines a first set of computational mechanisms that construct relations from the spatial arrangement, use, and storage of data items. A second set of computational mechanisms takes advantage of these relations by helping users to keep track of, search for, exchange, arrange, and visualize data items. The computational mechanisms are both adaptive and evocative, meaning that the computational mechanisms dynamically adapt to users and changing circumstances while also trying to influence the human sense-making process. Contributions: 1. Demonstration that computer systems can discover probable relations among data items from their spatial arrangement and use by users. This work identifies and analyzes various human mental processes involved in the determination of possible relations among data items such as documents on a work desk or files in a computer system. A computational equivalent is proposed for every mental process en_US
dc.description.statementofresponsibility by Paul Erich Keel. en_US
dc.format.extent 132 leaves en_US
dc.format.extent 10925222 bytes
dc.format.extent 10942293 bytes
dc.format.mimetype application/pdf
dc.format.mimetype application/pdf
dc.language.iso en_US
dc.publisher Massachusetts Institute of Technology en_US
dc.rights 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. en_US
dc.rights.uri http://dspace.mit.edu/handle/1721.1/7582
dc.subject Architecture. en_US
dc.title Knowledge trading : computational support for individual and collaborative sense-making activities en_US
dc.type Thesis en_US
dc.description.degree Ph.D. en_US
dc.contributor.department Massachusetts Institute of Technology. Dept. of Architecture. en_US
dc.identifier.oclc 60314500 en_US


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