Rough set based clustering for finding relevant document /
Searching for relevant documents based on the keywords of particular selected articles are proposed in this thesis. This method is proposed to help user get relevant document based on the articles they selected. The common searching engine will return up to thousand articles where some articles are...
| Main Author: | |
|---|---|
| Format: | Undergraduates Project Papers |
| Language: | English |
| Published: |
2013
|
| Subjects: | |
| Online Access: | http://umpir.ump.edu.my/id/eprint/7289/1/Rough_set_based_clustering_for_finding_relevant_document.pdf |
| _version_ | 1796990250658037760 |
|---|---|
| author | Ching, Ng Choon |
| author_facet | Ching, Ng Choon |
| author_sort | Ching, Ng Choon |
| collection | UMP |
| description | Searching for relevant documents based on the keywords of particular selected articles are proposed in this thesis. This method is proposed to help user get relevant document based on the articles they selected. The common searching engine will return up to thousand articles where some articles are not really relevant to the searching too. In this paper, rough set-based data mining technique is employed to enhance the result of searching relevant documents. The rough set-based clustering technique, namely MinMin Roughness (MMR) is applied to cluster documents from Wikipedia into groups according to keywords of selected articles in the effort for finding relevant documents. This research is done using dataset of articles from online Wikipedia website. The proposed keywords methods for finding relevant documents will save time during searching progress. This research is expected to be useful for finding relevant documents. |
| first_indexed | 2024-03-06T11:48:48Z |
| format | Undergraduates Project Papers |
| id | UMPir7289 |
| institution | Universiti Malaysia Pahang |
| language | English |
| last_indexed | 2024-03-06T11:48:48Z |
| publishDate | 2013 |
| record_format | dspace |
| spelling | UMPir72892021-06-17T01:19:14Z http://umpir.ump.edu.my/id/eprint/7289/ Rough set based clustering for finding relevant document / Ching, Ng Choon QA Mathematics Searching for relevant documents based on the keywords of particular selected articles are proposed in this thesis. This method is proposed to help user get relevant document based on the articles they selected. The common searching engine will return up to thousand articles where some articles are not really relevant to the searching too. In this paper, rough set-based data mining technique is employed to enhance the result of searching relevant documents. The rough set-based clustering technique, namely MinMin Roughness (MMR) is applied to cluster documents from Wikipedia into groups according to keywords of selected articles in the effort for finding relevant documents. This research is done using dataset of articles from online Wikipedia website. The proposed keywords methods for finding relevant documents will save time during searching progress. This research is expected to be useful for finding relevant documents. 2013 Undergraduates Project Papers NonPeerReviewed application/pdf en http://umpir.ump.edu.my/id/eprint/7289/1/Rough_set_based_clustering_for_finding_relevant_document.pdf Ching, Ng Choon (2013) Rough set based clustering for finding relevant document /. Faculty of Computer System & Software Engineering, Universiti Malaysia Pahang. |
| spellingShingle | QA Mathematics Ching, Ng Choon Rough set based clustering for finding relevant document / |
| title | Rough set based clustering for finding relevant document / |
| title_full | Rough set based clustering for finding relevant document / |
| title_fullStr | Rough set based clustering for finding relevant document / |
| title_full_unstemmed | Rough set based clustering for finding relevant document / |
| title_short | Rough set based clustering for finding relevant document / |
| title_sort | rough set based clustering for finding relevant document |
| topic | QA Mathematics |
| url | http://umpir.ump.edu.my/id/eprint/7289/1/Rough_set_based_clustering_for_finding_relevant_document.pdf |
| work_keys_str_mv | AT chingngchoon roughsetbasedclusteringforfindingrelevantdocument |