Best-match retrieval of sequential information
This dissertation reports an investigation into a number of search and retrieval techniques for new generation of information retrieval systems. It discusses the use of automatic indexing techniques to obtain document and query representatives, this includes methods for the selection of terms from d...
Saved in:
Main Author: | |
---|---|
Other Authors: | |
Format: | Theses and Dissertations |
Language: | English |
Published: |
2009
|
Subjects: | |
Online Access: | http://hdl.handle.net/10356/19564 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Nanyang Technological University |
Language: | English |
id |
sg-ntu-dr.10356-19564 |
---|---|
record_format |
dspace |
spelling |
sg-ntu-dr.10356-195642023-07-04T15:31:31Z Best-match retrieval of sequential information Singa Suparman. Cheng, Tee Hiang School of Electrical and Electronic Engineering DRNTU::Engineering::Electrical and electronic engineering::Computer hardware, software and systems This dissertation reports an investigation into a number of search and retrieval techniques for new generation of information retrieval systems. It discusses the use of automatic indexing techniques to obtain document and query representatives, this includes methods for the selection of terms from document texts and the use of conflation techniques to deal with variations in word forms. It also discusses the use of best match retrieval techniques as an alternative to Boolean retrieval mechanisms, which characterize current free-text retrieval (FTX) systems. This is foliowed by a description of term weighting techniques, which can be used to reflect the ability of search tenns to discriminate between relevant and non-relevant documents. Other techniques, which may, with further development, figure in future retrieval systems, are also briefly described. Master of Science (Communications and Computer Networking) 2009-12-14T06:15:30Z 2009-12-14T06:15:30Z 1997 1997 Thesis http://hdl.handle.net/10356/19564 en NANYANG TECHNOLOGICAL UNIVERSITY 109 p. application/pdf |
institution |
Nanyang Technological University |
building |
NTU Library |
continent |
Asia |
country |
Singapore Singapore |
content_provider |
NTU Library |
collection |
DR-NTU |
language |
English |
topic |
DRNTU::Engineering::Electrical and electronic engineering::Computer hardware, software and systems |
spellingShingle |
DRNTU::Engineering::Electrical and electronic engineering::Computer hardware, software and systems Singa Suparman. Best-match retrieval of sequential information |
description |
This dissertation reports an investigation into a number of search and retrieval techniques for new generation of information retrieval systems. It discusses the use of automatic indexing techniques to obtain document and query representatives, this includes methods for the selection of terms from document texts and the use of conflation techniques to deal with variations in word forms. It also discusses the use of best match retrieval techniques as an alternative to Boolean retrieval mechanisms, which characterize current free-text retrieval (FTX) systems. This is foliowed by a description of term weighting techniques, which can be used to reflect the ability of search tenns to discriminate between relevant and non-relevant documents. Other techniques, which may, with further development, figure in future retrieval systems, are also briefly described. |
author2 |
Cheng, Tee Hiang |
author_facet |
Cheng, Tee Hiang Singa Suparman. |
format |
Theses and Dissertations |
author |
Singa Suparman. |
author_sort |
Singa Suparman. |
title |
Best-match retrieval of sequential information |
title_short |
Best-match retrieval of sequential information |
title_full |
Best-match retrieval of sequential information |
title_fullStr |
Best-match retrieval of sequential information |
title_full_unstemmed |
Best-match retrieval of sequential information |
title_sort |
best-match retrieval of sequential information |
publishDate |
2009 |
url |
http://hdl.handle.net/10356/19564 |
_version_ |
1772826221727449088 |