2026-06-24T06:46:34Z https://meral.edu.mm/oai

oai:meral.edu.mm:recid/4917 2021-12-13T03:37:29Z 1582963302567:1597824273898 user-ucsy

Web Page Categorization Based on Content and Data Extraction for Academic Community Phyu, Sabai Linn, Khaing Wah Wah The web is a large amount of data and difficult tosearch information or data of user interest (ITacademic field). Therefore, it needs to categorize formeet user’s interesting field easily. Web pagecategorization help improve the quality of web search.In this paper, we proposed a framework for web dataextraction by using categorized web pages to improvedata extraction accuracy and result. Firstly, thenumbers of test web pages are defined as inputs. Weuse page segmentation algorithm (VIPS) to performsegmentation these pages to achieve content structurefor web page cleaning and to evaluate informative ormain content block. These main contents arecategorized by using Support Vector Machine (SVM)which gives accurate and efficient result. Thesecategorized web pages are stored into the database(IT library) to output data accurately when user query. 2014-02-17 http://hdl.handle.net/20.500.12678/0000004917 https://meral.edu.mm/records/4917