Work Description

Title: Semantic-Based Document Retrieval Using Spatial Distributions of Concepts Open Access Deposited

h
Attribute Value
Methodology
  • This dataset consists of 30 pages from Wikipedia: 10 pages discussing dogs, 10 pages discussing computers, and 10 pages discussing sports.
Description
  • This dataset was used for a proof-of-concept of fixed lexical chain approach for semantic information retrieval.
Creator
Depositor
  • wgrosky@umich.edu
Contact information
Discipline
Keyword
Date coverage
  • 2016-05-01 to 2017-03-01
Resource type
Last modified
  • 05/18/2018
Published
  • 02/26/2017
Language
DOI
  • https://doi.org/10.7302/Z26W980B
License
To Cite this Work:
Grosky, W. I., Ruas, T. L. (2017). Semantic-Based Document Retrieval Using Spatial Distributions of Concepts [Data set], University of Michigan - Deep Blue Data. https://doi.org/10.7302/Z26W980B

Relationships

This work is not a member of any user collections.

Files (Count: 1; Size: 1.73 MB)

Thumbnailthumbnail-column Title Original Upload Last Modified File Size Access Actions
WikipediaPages.zip 2017-02-26 2017-02-26 1.73 MB Open Access

Download All Files (To download individual files, select them in the “Files” panel above)

Best for data sets < 3 GB. Downloads all files plus metadata into a zip file.



Best for data sets > 3 GB. Globus is the platform Deep Blue Data uses to make large data sets available.   More about Globus

Remediation of Harmful Language

The University of Michigan Library aims to describe library materials in a way that respects the people and communities who create, use, and are represented in our collections. Report harmful or offensive language in catalog records, finding aids, or elsewhere in our collections anonymously through our metadata feedback form. More information at Remediation of Harmful Language.