{"id":{"repo_id":"mit","oai_identifier":"oai:dspace.mit.edu:1721.1/16846"},"canonical_url":"https://search.dev.ndltd.org/etd/mit/oai:dspace.mit.edu:1721.1/16846","repository":{"repo_id":"mit","name":"MIT","base_url":"https://dspace.mit.edu/oai/request"},"display":{"title":"Exploiting E-mail structure to improve summarization","abstract":"For this thesis, I designed and implemented a system to summarize e-mail messages. The system exploits two aspects of e-mail, thread reply chains and commonly-found features, to generate summaries. The system uses existing software designed to summarize single text documents. Such software typically performs best on well-authored, formal documents. E-mail messages, however, are typically neither well-authored, nor formal. As a result, existing summarization software typically gives a poor summary of e-mail messages. To remedy this poor performance, the system's approach preprocesses e-mail messages to synthesize new input to this software, so that it will output more useful summaries of e-mail. This pre-processing involves a lightweight, heuristics-based approach to filtering e-mail to remove e-mail signatures, header fields, and quoted parent messages. I also present a heuristics-based approach to identifying and reporting names, dates, and companies found in e-mail messages. Lastly, I discuss conclusions from a pilot user study of my summarization system, and conclude with areas for further investigation.","abstract_html":"For this thesis, I designed and implemented a system to summarize e-mail messages. The system exploits two aspects of e-mail, thread reply chains and commonly-found features, to generate summaries. The system uses existing software designed to summarize single text documents. Such software typically performs best on well-authored, formal documents. E-mail messages, however, are typically neither well-authored, nor formal. As a result, existing summarization software typically gives a poor summary of e-mail messages. To remedy this poor performance, the system's approach preprocesses e-mail messages to synthesize new input to this software, so that it will output more useful summaries of e-mail. This pre-processing involves a lightweight, heuristics-based approach to filtering e-mail to remove e-mail signatures, header fields, and quoted parent messages. I also present a heuristics-based approach to identifying and reporting names, dates, and companies found in e-mail messages. Lastly, I discuss conclusions from a pilot user study of my summarization system, and conclude with areas for further investigation.","abstract_has_math":false,"creators":["Lam, Derek Scott, 1979-"],"institution":"Massachusetts Institute of Technology","degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":"Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science.","school":null,"contributors":[],"advisors":["Steven L. Rohall and Chris Schmandt."],"committee_chairs":[],"committee_members":[],"year":2002,"date_issued":"2002","date_published":"2002","updated_at":"2026-07-22T22:21:23Z","subjects":["Electrical Engineering and Computer Science."],"languages":["eng"],"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. 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This pre-processing involves a lightweight, heuristics-based approach to filtering e-mail to remove e-mail signatures, header fields, and quoted parent messages. I also present a heuristics-based approach to identifying and reporting names, dates, and companies found in e-mail messages. Lastly, I discuss conclusions from a pilot user study of my summarization system, and conclude with areas for further investigation."]},{"key":"dc:description.degree","label":"Dc Description Degree","values":["M.Eng."]},{"key":"dc:format.mimetype","label":"Dc Format Mimetype","values":["application/pdf"]},{"key":"dc:title","label":"Title","values":["Exploiting E-mail structure to improve summarization"]}]}],"canonical_facts":{"dc:contributor.advisor":["Steven L. Rohall and Chris Schmandt."],"dc:contributor.department":["Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science."],"dc:contributor.other":["Massachusetts Institute of Technology. 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E-mail messages, however, are typically neither well-authored, nor formal. As a result, existing summarization software typically gives a poor summary of e-mail messages. To remedy this poor performance, the system's approach preprocesses e-mail messages to synthesize new input to this software, so that it will output more useful summaries of e-mail. This pre-processing involves a lightweight, heuristics-based approach to filtering e-mail to remove e-mail signatures, header fields, and quoted parent messages. I also present a heuristics-based approach to identifying and reporting names, dates, and companies found in e-mail messages. 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