Papers by Hmway Hmway Tar
World Academy of Science, Engineering and Technology, International Journal of Computer, Electrical, Automation, Control and Information Engineering, Sep 21, 2011
Documents clustering become an essential technology with the popularity of the Internet. Clusteri... more Documents clustering become an essential technology with the popularity of the Internet. Clustering has been very popular for a long time because it provides unique ways of digesting and generalizing large amounts of information. As most of the recent text clustering research focuses on addressing specific issues (e.g., feature selection and dimensionality reduction), very few new approaches are being devised. The existing clustering technology mainly focuses on term weight calculation. To achieve more accurate document clustering, more informative features including concept weight are important based on the Semantic technologies. Feature Selection is important for clustering process because some of the irrelevant or redundant feature may misguide the clustering results. To counteract this issue, the proposed system presents the concept weight for text clustering system developed based on a k-means algorithm in accordance with the principles of ontology so that the important of words of a cluster can be identified by the weight values. To a certain extent, it has resolved the semantic problem in specific areas. The experimental results performed using dissertations papers from Google Search Engine and the proposed method demonstrated its effectiveness and practical value.
Fifth Local Conference on Parallel and Soft Computing, Dec 16, 2010
Documents clustering become an essential technology with the popularity of the Internet. That als... more Documents clustering become an essential technology with the popularity of the Internet. That also means that fast and high-quality document clustering technique play core topics. Text clustering or shortly clustering is about discovering semantically related groups in an unstructured collection of documents. Clustering has been very popular for a long time because it provides unique ways of digesting and generalizing large amounts of information. One of the issues of clustering is to extract proper feature (concept) of a problem domain. The existing clustering technology mainly focuses on term weight calculation. To achieve more accurate document clustering, more informative features including concept weight are important. Feature Selection is important for clustering process because some of the irrelevant or redundant feature may misguide the clustering results. To counteract this issue, the proposed system presents the concept weight for text clustering system developed based on ...
2017 International Conference on Intelligent Informatics and Biomedical Sciences (ICIIBMS), 2017
This paper presented a novel approach for document clustering applying cloud technologies for the... more This paper presented a novel approach for document clustering applying cloud technologies for the system's performance issue. It is critical for application service in cloud computing to provide precise information. Ontology servicing is one of the methods to deal with semantic ambiguity and information overload efficiently through appropriate semantic models and semantic technology. This system is the advanced and extended version of the system we have been published before. The experiments reveal that even the testing documents increased; the system may actually be able to produce useful result for text document clustering. In this paper, we propose a cloud service that exploits a novel ontology-based technique for identifying cloud service to improve the accuracy of cloud services searching. Our approach has the capability to perform cloud service concepts from cloud service sources. The main idea behind our method is cloud services using an ontology-based technique.
Advances in Intelligent Systems and Computing, 2015
With the increasing amount of information, researchers in digital communities have witnessed the ... more With the increasing amount of information, researchers in digital communities have witnessed the tremendous growth of publications. The overwhelming amount of information still makes it a time-consuming task. There are many of computer science and medical subject related documents cited on the Internet. Ontologies currently are hot topics in the area of Semantic Web. Ontologies can also help in addressing the problem of searching related entities, including research publications. The purpose of the system is to cluster the text documents based upon the ontology. The system is applying the modified concept weighting and become the extended version of the work that has been done before [8]. After the time passed the testing amount of data becomes lager and the challenges is the time complexity. To overcome this issue the system used the scoring method at the concept weighting stages to manage the time complexity. The experiments reveal that even the testing documents increased; the system may actually be able to produce useful result for text document clustering.
International Journal of Applied Information Systems, 2013
Incorporating semantic knowledge from ontology into text document clustering is an important but ... more Incorporating semantic knowledge from ontology into text document clustering is an important but challenging problem. Moreover, there are many of computer science and medical based subject related papers and journals cited on the Internet. The purpose of this system is to cluster the documents based upon the statistical method and from the semantic web point of view, the system advances in the field of scientific endeavor. Moreover this system is the advanced and extended version of the paper we have been published before. After time passed the testing data amount becomes lager and lager and we have been found that our previous methods should have to improve in more mathematically. Finally, it also reports on the experiments that performed to test the system utilization weighting scheme which is used to encode the importance of concepts inside documents. For the experiments the system has to use ontology that enables us to describe and organize this from heterogeneous sources, and to cluster about it. The experiments reveal that even the testing documents increased; the system may actually be able to produce useful results.
Ontologies currently are a hot topic in the areas of Semantic Web. The current clustering researc... more Ontologies currently are a hot topic in the areas of Semantic Web. The current clustering research emphasizes the development of a more efficient clustering method and mainly focuses on term weight calculation without considering the domain knowledge. This paper investigates how ontologies can also be applied to the clustering process. To complement the traditional clustering method, more informative features including concept weight are important based on recent developments in the area of the Semantic technologies. The proposed system presents the concept weight for text clustering system developed based on a k-means algorithm in accordance with the principles of ontology so that the important of words of a cluster can be identified by the weighted values. To a certain extent, it has resolved the semantic progeny in specific areas. The experimental results performed using dissertations papers from Google Search Engine and the proposed method demonstrated its effectiveness and practical value.
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Papers by Hmway Hmway Tar