Web Data ETL System with Unsupervised Extraction

• Main Authors: Yu-An Chou, 周昱安
• Other Authors: Chia-Hui Chang
• Format: Others
• Language: zh-TW
• Published: 2018
• Online Access: http://ndltd.ncl.edu.tw/handle/d5yn85

碩士 === 國立中央大學 === 軟體工程研究所 === 106 === Web is the most important and primary way for fetching information nowadays, especially in deep web. In web data extraction, the page level approach compared with the record level approach is a more comprehensive solution because it can generate more complete page schema for extracting all the data of page. Otherwise, most research of web data extraction is focusing on algorithm of schema induction or extraction, instead of user-end service. Therefore, the research of this paper provide a ETL(extract-transform-load) system with automated crawler which base on unsupervised extraction. The users can extract and output (e.g. API endpoint, static export) web data by user-friend GUI, without any programming. Hoping the research can simplify the management of the entire complex process and bring convenience web data extraction to the general public.