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oai:dspace.mit.edu:1721.1/774382022-01-13T07:54:29Zcom_1721.1_7582com_1721.1_7581com_1721.1_104841col_1721.1_131023col_1721.1_141484

Patrick H. Winston. Krakauer, Caryn E. (Caryn Elizabeth) Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science. Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science 2013-03-01T15:04:49Z 2013-03-01T15:04:49Z 2012 2012 http://hdl.handle.net/1721.1/77438 826502735 Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2012. Cataloged from PDF version of thesis. Includes bibliographical references (p. 55). To understand a new situation, humans draw from their knowledge of past experiences and events. For a computer to use the same method, it must be able to retrieve stories that shed light on a new situation. Traditional story retrieval uses keywords to determine similarity. Keywords are useful for determining whether stories share similar topics. However, they miss how stories can be structurally similar. In my work, I have used high level concept patterns, which are structures of causally related events. Concept patterns follow the Goldilocks principle, that the features should be of intermediate size. Given a story about cyber crime and another about traditional warfare, the wording will be different, as cyber crime involves viruses, DDOS attacks, and hacking, while traditional warfare involves armies, invasions, and weapons. However, both stories may involve instances of revenge and betrayal. Using a corpus of 15 conflict stories, I have shown that a similarity measure based on concept patterns differs substantially from a similarity measured based on keywords. In addition, I compared three concept-pattern methods with human performance in a pilot study in which 11 participants performed story comparison. My goal was to contribute to a human competence model, but I have also explored applications in story retrieval, prediction, explanation, and grouping. by Caryn E. Krakauer. M.Eng. 70 p. eng Massachusetts Institute of Technology 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 Electrical Engineering and Computer Science. Story retrieval and comparison using concept patterns Thesis application/pdf false Publication unknown unknown <Publication xmlns="https://www.openaire.eu/cerif-profile/1.1/" id="29aae6c4-8984-46f6-a8ee-0c78bd0cca79"> <Type xmlns="https://www.openaire.eu/cerif-profile/vocab/COAR_Publication_Types">http://purl.org/coar/resource_type/c_1843</Type> <Language>eng</Language> <Title>Story retrieval and comparison using concept patterns</Title> <PublishedIn> <Publication> </Publication> </PublishedIn> <PublicationDate>2012</PublicationDate> <Authors> <Author> <DisplayName>Krakauer, Caryn E. (Caryn Elizabeth)</DisplayName> <Affiliation> <OrgUnit> </OrgUnit> </Affiliation> </Author> </Authors> <Editors> </Editors> <Publishers> <Publisher> <DisplayName>Massachusetts Institute of Technology</DisplayName> <OrgUnit /> </Publisher> </Publishers> <License>http://dspace.mit.edu/handle/1721.1/7582</License> <Keyword>Electrical Engineering and Computer Science.</Keyword> <Abstract>To understand a new situation, humans draw from their knowledge of past experiences and events. For a computer to use the same method, it must be able to retrieve stories that shed light on a new situation. Traditional story retrieval uses keywords to determine similarity. Keywords are useful for determining whether stories share similar topics. However, they miss how stories can be structurally similar. In my work, I have used high level concept patterns, which are structures of causally related events. Concept patterns follow the Goldilocks principle, that the features should be of intermediate size. Given a story about cyber crime and another about traditional warfare, the wording will be different, as cyber crime involves viruses, DDOS attacks, and hacking, while traditional warfare involves armies, invasions, and weapons. However, both stories may involve instances of revenge and betrayal. Using a corpus of 15 conflict stories, I have shown that a similarity measure based on concept patterns differs substantially from a similarity measured based on keywords. In addition, I compared three concept-pattern methods with human performance in a pilot study in which 11 participants performed story comparison. My goal was to contribute to a human competence model, but I have also explored applications in story retrieval, prediction, explanation, and grouping.</Abstract> <Access xmlns="http://purl.org/coar/access_right" > </Access> </Publication>