Information extraction for online review mining
In this FYP report, the design and implementation of information extraction for online review mining are presented. The report explains the architecture of the overall system, the design of the database and the decision made during the web service design and database selection. The report foc...
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2013
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sg-ntu-dr.10356-518822023-03-03T20:48:50Z Information extraction for online review mining Pang, Zineng. Chang Kuiyu School of Computer Engineering Centre for Advanced Information Systems DRNTU::Engineering::Computer science and engineering::Information systems::Information systems applications In this FYP report, the design and implementation of information extraction for online review mining are presented. The report explains the architecture of the overall system, the design of the database and the decision made during the web service design and database selection. The report focuses on the design of the two information extractors. The first one is the review extractor which consists of review crawling, data analysing and data storing. The feature extractor, on the other hand, directly extracts feature information from the source website and links them to the product in the database. The secondary focus of the report is on the design of the database schema. The database contains multiple categories of data and different indexing menthod, such that it could be used by other member of the team to generate dynamic diagrams and product analysis report. Bachelor of Engineering (Computer Science) 2013-04-15T04:19:19Z 2013-04-15T04:19:19Z 2013 2013 Final Year Project (FYP) http://hdl.handle.net/10356/51882 en Nanyang Technological University 33 p. application/pdf |
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DRNTU::Engineering::Computer science and engineering::Information systems::Information systems applications Pang, Zineng. Information extraction for online review mining |
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In this FYP report, the design and implementation of information extraction for online review mining are presented. The report explains the architecture of the overall system, the design of the database and the decision made during the web service design and database selection.
The report focuses on the design of the two information extractors. The first one is the review extractor which consists of review crawling, data analysing and data storing. The feature extractor, on the other hand, directly extracts feature information from the source website and links them to the product in the database.
The secondary focus of the report is on the design of the database schema. The database contains multiple categories of data and different indexing menthod, such that it could be used by other member of the team to generate dynamic diagrams and product analysis report. |
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Chang Kuiyu |
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Chang Kuiyu Pang, Zineng. |
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Final Year Project |
author |
Pang, Zineng. |
author_sort |
Pang, Zineng. |
title |
Information extraction for online review mining |
title_short |
Information extraction for online review mining |
title_full |
Information extraction for online review mining |
title_fullStr |
Information extraction for online review mining |
title_full_unstemmed |
Information extraction for online review mining |
title_sort |
information extraction for online review mining |
publishDate |
2013 |
url |
http://hdl.handle.net/10356/51882 |
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1759856672816234496 |