Web data mining on XML documents

The World Wide Web has become the largest and most convenient source of information. Searching and using Web data is becoming an important part in people's work and daily life. The need for collecting, extracting and analyzing information from the WWW is increasing. However, data existing on th...

Full description

Saved in:
Bibliographic Details
Main Author: Wen, Yi.
Other Authors: Ng, Wee Keong
Format: Theses and Dissertations
Published: 2008
Subjects:
Online Access:http://hdl.handle.net/10356/2529
Tags: Add Tag
No Tags, Be the first to tag this record!
Institution: Nanyang Technological University
id sg-ntu-dr.10356-2529
record_format dspace
spelling sg-ntu-dr.10356-25292023-03-04T00:33:36Z Web data mining on XML documents Wen, Yi. Ng, Wee Keong School of Computer Engineering DRNTU::Engineering::Computer science and engineering::Information systems::Information storage and retrieval The World Wide Web has become the largest and most convenient source of information. Searching and using Web data is becoming an important part in people's work and daily life. The need for collecting, extracting and analyzing information from the WWW is increasing. However, data existing on the Web is unstructured. The lack of structures in Web documents render traditional database techniques inapplicable for managing Web data. The advent of the extensible Markup Language(XML) has enabled flexible structuring of Web data. An XML document uses meaningful tags to provide semantic information for different parts of the document. An XML document is valid when it has a Document Type Definition(DTD) to describe its schema. An important issue for Web data mining is efficiently extracting data from Web documents and organize it into a proper form for data mining. Our work aims at extracting and transforming the Web data into a proper form such that they can be analyzed in a similar way as data mining in relational databases. Master of Engineering (SCE) 2008-09-17T09:04:49Z 2008-09-17T09:04:49Z 2000 2000 Thesis http://hdl.handle.net/10356/2529 Nanyang Technological University application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
topic DRNTU::Engineering::Computer science and engineering::Information systems::Information storage and retrieval
spellingShingle DRNTU::Engineering::Computer science and engineering::Information systems::Information storage and retrieval
Wen, Yi.
Web data mining on XML documents
description The World Wide Web has become the largest and most convenient source of information. Searching and using Web data is becoming an important part in people's work and daily life. The need for collecting, extracting and analyzing information from the WWW is increasing. However, data existing on the Web is unstructured. The lack of structures in Web documents render traditional database techniques inapplicable for managing Web data. The advent of the extensible Markup Language(XML) has enabled flexible structuring of Web data. An XML document uses meaningful tags to provide semantic information for different parts of the document. An XML document is valid when it has a Document Type Definition(DTD) to describe its schema. An important issue for Web data mining is efficiently extracting data from Web documents and organize it into a proper form for data mining. Our work aims at extracting and transforming the Web data into a proper form such that they can be analyzed in a similar way as data mining in relational databases.
author2 Ng, Wee Keong
author_facet Ng, Wee Keong
Wen, Yi.
format Theses and Dissertations
author Wen, Yi.
author_sort Wen, Yi.
title Web data mining on XML documents
title_short Web data mining on XML documents
title_full Web data mining on XML documents
title_fullStr Web data mining on XML documents
title_full_unstemmed Web data mining on XML documents
title_sort web data mining on xml documents
publishDate 2008
url http://hdl.handle.net/10356/2529
_version_ 1759856705755152384