Case based reasoning for XML tags recommendation

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Name: Sutheetutt Vacharaskunee

LCSH: Reasoning.

LCSH: XML (Document markup language)

Othors: Computer Science -- Thesis (Degree of Doctor)

Othors: King Mongkut's Institute of Technology Ladkrabang. -- Computer Science -- Thesis.

Abstract: XML is a markup language that allows document owners to describe their data by specifying their own formats including structure and tag. There might be the same information which is in the same domain described in different formats. This includes using different tag names that has the same meaning and/or using different tags hierarchy order. The main problem when searching information from these XML documents which are in the same domain is that cannot retrieve all relevant information by using only one format. The best way of retrieve all relevant information is XML documents which are in the same domain use the same tags. Recently, there are many researches on this area. However, none of them can handle this problem perfectly. The purpose of this thesis is to handle this problem by using Case Based Reasoning (CBR). CBR is a powerful problem solving method that uses past experience to be knowledge for solving new problems. In this case, the knowledge from CBR will make XML tag recommendation more efficiency. This thesis introduces CBR for XML Tags Recommendation (XTR). The recommend tag is the most popular word from the group of the same meaning words. User inputs XML path into XTR. Then, it finds similar cases and recommends the best solution from the retrieve case to the user. The result will be collected in the knowledge base. To compare the same meaning words, XTR uses WordNet which is one of the most famous thesaurus. For the most popular word, WordCount which contains the most frequency use English words has been used. In XML path matching, XTR uses a method that has been developed in this thesis.

King Mongkut's Institute of Technology Ladkrabang. Central Library

Address: Bangkok

Email: Lifelong@kmitl.ac.th

Name: Sarun Intakosum

Role: Thesis Advisor

Email : kisarun@kmitl.ac.th

Created: 2014

Modified: 2558-10-05

Issued: 2015-10-05

วิทยานิพนธ์/Thesis

application/pdf

CallNumber: Thesis S95c 2014

eng

DegreeName: Doctor of Philosophy (Computer Science)

Level: Doctoral Degree

Descipline: Computer Science

Grantor: King Mongkut's Institute of Technology Ladkrabang

©copyrights King Mongkut's Institute of Technology Ladkrabang

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