Repository logo
Log in(current)
Repository logoMIT Open ScholarshipDSpace@MIT
  1. Home
  2. MIT Libraries
  3. MIT Theses
  4. Graduate Theses
  5. Automatic classification of documents with an in-depth analysis of information extraction and automatic summarization

Automatic classification of documents with an in-depth analysis of information extraction and automatic summarization

Thumbnail Image
Download
Name

56138579-MIT.pdf

Description
Full printable version
Size

8.04 MB

Format

Adobe PDF

Checksum (MD5)

8f68355ef6607f27f1981ea47562c922

Author(s)
Hohm, Joseph Brandon, 1982-
Advisor(s)
John R. Williams.
Date Issued
2004
Publisher
Massachusetts Institute of Technology
Abstract
Today, annual information fabrication per capita exceeds two hundred and fifty megabytes. As the amount of data increases, classification and retrieval methods become more necessary to find relevant information. This thesis describes a .Net application (named I-Document) that establishes an automatic classification scheme in a peer-to-peer environment that allows free sharing of academic, business, and personal documents. A Web service architecture for metadata extraction, Information Extraction, Information Retrieval, and text summarization is depicted. Specific details regarding the coding process, competition, business model, and technology employed in the project are also discussed.
Description
Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Civil and Environmental Engineering, 2004.
Includes bibliographical references (leaves 78-80).
Subjects
Civil and Environmental Engineering.
MIT Department
Massachusetts Institute of Technology. Department of Civil and Environmental Engineering
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
Persistent DSpace Link
http://hdl.handle.net/1721.1/29415
Repository logo
PrivacyPermissionsAccessibilityContact us
Repository logo
Notify us about copyright concerns.