KMITL

Permanent URI for this communityhttps://dspace.kmitl.ac.th/handle/123456789/1

Browse

Search Results

Now showing 1 - 6 of 6

Some of the metrics are blocked by your
consent settings
A method of recommendation the most used XML tags
(2014-01-01)
Vacharaskunee, Sutheetutt
;
Intakosum, Sarun
Processing of a large data set which is known for today as big data processing is still a problem that has not yet a well-defined solution. The data can be both structured and unstructured. For the structured part, eXtensible Markup Language (XML) is a major tool that freely allows document owners to describe and organize their data using their markup tags. One major problem, however, behind this freedom lies in the big data retrieving process. The same or similar information that are described using the different tags or different structures may not be retrieved if the query statements contains different keywords to the one used in the markup tags. The best way to solve this problem is to specify a standard set of the markup tags for each problem domain. The creation of such a standard set if done manually requires a lot of hard work and is a time consuming process. In addition, it may be hard to define terms that are acceptable by all people. This research proposes a model for a new technique, "XML Tag Recommendation" (XTR) that aims to solve this problem. This technique applies the idea of Case Base Reasoning (CBR) by collecting the most used tags in each domain as a case. These tags come from the collection of related words in WordNet. The WordCount that is the web site to find the frequency of words is applied to choose the most used one. The input (problem) to the XTR system is an XML document contains the tags specified by the document owners. The solution is a set of the recommended tags, which is the most used tags, for the problem domain of the document. Document owners have a freedom to change or not change the tags in their documents and can provide feedback to the XTR system. © (2014) Trans Tech Publications, Switzerland.
Some of the metrics are blocked by your
consent settings
An approach to XML tag recommendation
(2011-01-01)
Vacharaskunee, Sutheetutt
;
Intakosum, Sarun
The one strong point of XML is that it allows document owners to create their own structure and tag names. It might be that some XML documents contain the same information but use a different structure and/or tag names that have the same meaning but in different words. It will be difficult not only to search all relevant information in one query but also to use exchanged information right away. If the sender and receiver use different formats of XML, then either the sender or receiver has to reformat his XML. The best way to make searching and/or exchanging information easier is to ensure that all XML documents are in the same format. XML Tag Recommendation (XTR) is introduced to support this idea. XTR is based on case-based reasoning framework. It collects the most used tag name as a solution for future use. When you insert a new problem to XTR, it finds the most similar case and recommends the solution from that case to the XML document owner. The XML document owner can change his document format into the recommended solution format. Thus, the XML documents are in the same format. This makes searching and/or exchanging information more powerful. © 2011 IEEE.
Some of the metrics are blocked by your
consent settings
XML document recommendation by using case based reasoning
(2010-09-01)
Vacharaskunee, Sutheetutt
;
Intakosum, Sarun
Case Based Reasoning (CBR) is the process of solving new problem based on the solutions of similar previous problems. XML is a markup language that allows document owners describe their data in their own formats. There might be the same information has been described in various ways. This makes searching those information from different formats difficult. CXDR (CBR for XML Document Recommendation) is an idea to make searching XML documents easier. CXDR applies CBR framework to collect the mostly use XML document and recommend it to its user. CBR in CXDR consists of two parts, cases and knowledge. The case is XML documents and the knowledge is an XML document recommendation. The recommendation from CXDR is the most use XML element names and structure. © 2010 IEEE.
Some of the metrics are blocked by your
consent settings
XML path matching for different hierarchy order of elements in XML documents
(2010-09-01)
Vacharaskunee, Sutheetutt
;
Intakosum, Sarun
XML documents allow document owners to create their documents in their own formats (element names and structure). The same information might be described in several ways. To find the similarity between XML documents which use different formats, one method is path similarity detection. The recently approach is PathSim. The previous approach can detect the similarity rate between two XML paths in case those two XML paths are in the same hierarchy order of elements that are semantic with each other. If XML documents use different elements hierarchy order, that approach has a low similarity rate. To improve the previous approach, PathMatch is introduced. PathMatch uses the edit distance algorithm to find the semantic similarity rate between element names and a cost matrix model to find the similarity rate between two XML paths. On the result, PathMatch has a higher similarity rate than the previous approach in case those two XML paths contain a different hierarchy order of elements that are semantic with each other. Moreover, in case two XML paths contain the same hierarchy order, PathMatch has the same similarity rate as the previous one. © 2010 IEEE.
Some of the metrics are blocked by your
consent settings
XER: A recommendation for XML element
(2010-08-11)
Vacharaskunee, Sutheetutt
;
Intakosum, Sarun
The strong point of the XML is that it allows document owners to describe their documents in their own format (structure and element names). There might be the same information has been describe in various ways. When user wants to search some information from XML documents, user might not retrieve all related results because of the difference of elements (tag names). To retrieve all related results, user needs to have queries for all possible elements. XML Element Recommendation (XER) is an idea to make XML documents easier for searching. It receives XML document as an input and compares that input with XML documents from database. It compares word similarity and semantic of each element. For semantic similarity of each element, it checks those elements to find which element (word) should be used by using word ranking (most common words). The output is a recommendation for each element of input XML document. © 2010 IEEE.
Some of the metrics are blocked by your
consent settings
XML element recommendation by semantic ranking
(2010-05-28)
Vacharaskunee, Sutheetutt
;
Intakosum, Sarun
From the strong point of XML that allows document owners to describe their documents in their own format, it is difficult to search information if those XML documents use different formats. Moreover, users might not retrieve all relevant information from differently formatted XML documents. To allow users to retrieve all relevant results, users need to have as many as queries for all possible formats. SXER (Semantic Ranking for XML Element Recommendation) is an idea to make XML documents easier for searching. It receives XML document as an input, checks all possible semantics for each element, and checks those semantic elements to find which element (word) should be used. The output is a recommendation for each element of input XML document. ©2010 IEEE.

KMITL

Browse

Filters

Settings

Sort By

Results per page

Search Results