An intelligent data mapping for hydrological information system (his) cube data base to cater from various data types

Information Extraction is a process that extracts information from existing system source and stores into a database. Previous researchers had focus on information extraction for HTML data using wrapper approach. The drawback from this approach is resiliency where wrapper fails to function when the...

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Main Authors: Selamat, Harihodin, Mohd. Rahim, Mohd. Shafry, Daman, Daut
Format: Monograph
Language:en
Published: Faculty of Computer Science and Information System 2004
Subjects:
Online Access:http://eprints.utm.my/4119/1/74074.pdf
http://eprints.utm.my/4119/
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author Selamat, Harihodin
Mohd. Rahim, Mohd. Shafry
Daman, Daut
author_facet Selamat, Harihodin
Mohd. Rahim, Mohd. Shafry
Daman, Daut
author_sort Selamat, Harihodin
building UTM Library
collection Institutional Repository
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
continent Asia
country Malaysia
description Information Extraction is a process that extracts information from existing system source and stores into a database. Previous researchers had focus on information extraction for HTML data using wrapper approach. The drawback from this approach is resiliency where wrapper fails to function when the file of interest structure changes. Ontology based information extraction is an alternative solution for this problem. In this research, ontology based information extraction used hydrological data from Jabatan Pengairan dan Saliran (JPS) as the case study. Ontology based information extraction for hydrology domain or also known as EkstrakPro is divided into three main processes; which are ontology parser process, keyword and sequences recognition process, and a data mapping process. EkstrakPro used two inputs; the hydrology data and ontology extraction. An important feature in EkstrakPro is that ontology extraction, where unit object is introduced to simplify the ontology maintenance. The sequential recognition algorithm is to solve the time consuming issues for extracting sequential data. Five types of hydrological data are used in the experiment. These data are divided into three categories; (i) original data taken from gauging machine, (ii) the altered data and (iii) the different sizes of data. Based on these categories, the information extraction resiliency and time taken have been measured using a precise equation and O-notation. The results show that prototype ˜EkstrakPro can extract different structure hydrology data correctly by using only one algorithm. Using sequential recognition algorithm can also further reduce the time required for extraction of information. The result of the research proves that information extraction can be solved using ontology approach.
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institution Universiti Teknologi Malaysia
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spelling my.utm.eprints-41192017-08-07T00:59:47Z http://eprints.utm.my/4119/ An intelligent data mapping for hydrological information system (his) cube data base to cater from various data types Selamat, Harihodin Mohd. Rahim, Mohd. Shafry Daman, Daut T Technology (General) Information Extraction is a process that extracts information from existing system source and stores into a database. Previous researchers had focus on information extraction for HTML data using wrapper approach. The drawback from this approach is resiliency where wrapper fails to function when the file of interest structure changes. Ontology based information extraction is an alternative solution for this problem. In this research, ontology based information extraction used hydrological data from Jabatan Pengairan dan Saliran (JPS) as the case study. Ontology based information extraction for hydrology domain or also known as EkstrakPro is divided into three main processes; which are ontology parser process, keyword and sequences recognition process, and a data mapping process. EkstrakPro used two inputs; the hydrology data and ontology extraction. An important feature in EkstrakPro is that ontology extraction, where unit object is introduced to simplify the ontology maintenance. The sequential recognition algorithm is to solve the time consuming issues for extracting sequential data. Five types of hydrological data are used in the experiment. These data are divided into three categories; (i) original data taken from gauging machine, (ii) the altered data and (iii) the different sizes of data. Based on these categories, the information extraction resiliency and time taken have been measured using a precise equation and O-notation. The results show that prototype ˜EkstrakPro can extract different structure hydrology data correctly by using only one algorithm. Using sequential recognition algorithm can also further reduce the time required for extraction of information. The result of the research proves that information extraction can be solved using ontology approach. Faculty of Computer Science and Information System 2004-09-30 Monograph NonPeerReviewed application/pdf en http://eprints.utm.my/4119/1/74074.pdf Selamat, Harihodin and Mohd. Rahim, Mohd. Shafry and Daman, Daut (2004) An intelligent data mapping for hydrological information system (his) cube data base to cater from various data types. Project Report. Faculty of Computer Science and Information System, Skudai, Johor. (Unpublished)
spellingShingle T Technology (General)
Selamat, Harihodin
Mohd. Rahim, Mohd. Shafry
Daman, Daut
An intelligent data mapping for hydrological information system (his) cube data base to cater from various data types
title An intelligent data mapping for hydrological information system (his) cube data base to cater from various data types
title_full An intelligent data mapping for hydrological information system (his) cube data base to cater from various data types
title_fullStr An intelligent data mapping for hydrological information system (his) cube data base to cater from various data types
title_full_unstemmed An intelligent data mapping for hydrological information system (his) cube data base to cater from various data types
title_short An intelligent data mapping for hydrological information system (his) cube data base to cater from various data types
title_sort intelligent data mapping for hydrological information system (his) cube data base to cater from various data types
topic T Technology (General)
url http://eprints.utm.my/4119/1/74074.pdf
http://eprints.utm.my/4119/
url_provider http://eprints.utm.my/