Log in
Language:

MERAL Myanmar Education Research and Learning Portal

  • Top
  • Universities
  • Ranking
To
lat lon distance
To

Field does not validate



Index Link

Index Tree

Please input email address.

WEKO

One fine body…

WEKO

One fine body…

Item

{"_buckets": {"deposit": "a0706f23-9aee-4c8a-a554-2ee686be2fca"}, "_deposit": {"id": "4048", "owners": [], "pid": {"revision_id": 0, "type": "recid", "value": "4048"}, "status": "published"}, "_oai": {"id": "oai:meral.edu.mm:recid/4048", "sets": ["user-ucsy"]}, "communities": ["ucsy"], "item_1583103067471": {"attribute_name": "Title", "attribute_value_mlt": [{"subitem_1551255647225": "Integrating FS Tree with Clustering for Mining Frequent Web Access Patterns", "subitem_1551255648112": "en"}]}, "item_1583103085720": {"attribute_name": "Description", "attribute_value_mlt": [{"interim": "Mining frequent patterns is an important component of many prediction systems. One common usage in web applications is the mining of users’ access behavior for the purpose of predicting and hence pre-fetching the web pages that the user is likely to visit.This paper presents web usage mining model for discovering frequent patterns in sequence databases that requires only two database scans. The first scan obtains support counts for subsequences of length. The second scan extracts potentially frequent sequences tree structure (FS-tree). Frequent sequence patterns are generated by mining the FS-tree. On the other hand, clustering methods are unsupervised methods, and normally are not used for classification directly. This paper involves incorporating clustering with FS-tree algorithm. The pre-processed data is divided into meaningful clusters then the clusters are used as training data for the FS-tree algorithm, to get higher accuracy."}]}, "item_1583103108160": {"attribute_name": "Keywords", "attribute_value": []}, "item_1583103120197": {"attribute_name": "Files", "attribute_type": "file", "attribute_value_mlt": [{"accessrole": "open_access", "date": [{"dateType": "Available", "dateValue": "2019-08-05"}], "displaytype": "preview", "download_preview_message": "", "file_order": 0, "filename": "55140.pdf", "filesize": [{"value": "390 Kb"}], "format": "application/pdf", "future_date_message": "", "is_thumbnail": false, "licensetype": "license_free", "mimetype": "application/pdf", "size": 390000.0, "url": {"url": "https://meral.edu.mm/record/4048/files/55140.pdf"}, "version_id": "6cab01ac-1222-4f6c-b57b-9c6dd1be710a"}]}, "item_1583103131163": {"attribute_name": "Journal articles", "attribute_value_mlt": [{"subitem_issue": "", "subitem_journal_title": "Fourth Local Conference on Parallel and Soft Computing", "subitem_pages": "", "subitem_volume": ""}]}, "item_1583103147082": {"attribute_name": "Conference papers", "attribute_value_mlt": [{"subitem_acronym": "", "subitem_c_date": "", "subitem_conference_title": "", "subitem_part": "", "subitem_place": "", "subitem_session": "", "subitem_website": ""}]}, "item_1583103211336": {"attribute_name": "Books/reports/chapters", "attribute_value_mlt": [{"subitem_book_title": "", "subitem_isbn": "", "subitem_pages": "", "subitem_place": "", "subitem_publisher": ""}]}, "item_1583103233624": {"attribute_name": "Thesis/dissertations", "attribute_value_mlt": [{"subitem_awarding_university": "", "subitem_supervisor(s)": [{"subitem_supervisor": ""}]}]}, "item_1583105942107": {"attribute_name": "Authors", "attribute_value_mlt": [{"subitem_authors": [{"subitem_authors_fullname": "Hlaing, Hnin Ei Ei"}, {"subitem_authors_fullname": "Khine, May Aye"}]}]}, "item_1583108359239": {"attribute_name": "Upload type", "attribute_value_mlt": [{"interim": "Publication"}]}, "item_1583108428133": {"attribute_name": "Publication type", "attribute_value_mlt": [{"interim": "Article"}]}, "item_1583159729339": {"attribute_name": "Publication date", "attribute_value": "2009-12-30"}, "item_1583159847033": {"attribute_name": "Identifier", "attribute_value": "http://onlineresource.ucsy.edu.mm/handle/123456789/1756"}, "item_title": "Integrating FS Tree with Clustering for Mining Frequent Web Access Patterns", "item_type_id": "21", "owner": "1", "path": ["1597824273898"], "permalink_uri": "http://hdl.handle.net/20.500.12678/0000004048", "pubdate": {"attribute_name": "Deposited date", "attribute_value": "2019-08-05"}, "publish_date": "2019-08-05", "publish_status": "0", "recid": "4048", "relation": {}, "relation_version_is_last": true, "title": ["Integrating FS Tree with Clustering for Mining Frequent Web Access Patterns"], "weko_shared_id": -1}
  1. University of Computer Studies, Yangon
  2. Conferences

Integrating FS Tree with Clustering for Mining Frequent Web Access Patterns

http://hdl.handle.net/20.500.12678/0000004048
http://hdl.handle.net/20.500.12678/0000004048
d90c9287-809d-44dd-8c93-bf24c94da44e
a0706f23-9aee-4c8a-a554-2ee686be2fca
None
Preview
Name / File License Actions
55140.pdf 55140.pdf (390 Kb)
Back
0
0
views
downloads
See details
Views Downloads

Versions

Ver.1 2020-09-01 13:59:53.659675
Show All versions

Share

Mendeley Twitter Facebook Print Addthis

Export

OAI-PMH
  • OAI-PMH DublinCore
Other Formats
  • JSON

Confirm


Back to MERAL


Back to MERAL