By Hiroshi Motoda
The necessity for amassing suitable info assets, mining priceless wisdom from diversified types of facts resources and briskly reacting to scenario swap is ever expanding. lively mining is a set of actions every one fixing part of this want, yet jointly attaining the mining aim throughout the spiral influence of those interleaving 3 steps. This e-book is a joint attempt from major and energetic researchers in Japan with a topic approximately lively mining and a well timed document at the vanguard of knowledge assortment, user-centered mining and person interaction/reaction. It bargains a latest evaluation of contemporary options with real-world functions, stocks hard-learned reports, and sheds gentle on destiny improvement of lively mining.
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Extra resources for Active Mining
PUM was implemented using Visual C++ and Ruby on Windows2000. 2 Region identification and update check PUM learns update monitoring rules to check partial updates in a Web page. The update monitoring rules consists of two kinds of rules: region identification rules and update check rules. Region identification (RI) rules are used to identify and extract a region in which a user wants to know its updates. Update check (UC) rules are utilized to determine whether the update is one which a user wants to know or not.
Then the system puts the query through to a search engine and obtains a hit-list. 2. Evaluation of results by a user: After getting a hit-list from a search engine, the system asks the user to evaluate and mark the relevancy (relevant or nonrelevant) of a small part of Web pages in the hit-list (usually upper 10 pages), and stores those pages as training pages, especially the relevant pages as positive training pages and the non-relevant pages as negative training pages. 3. Analyzing training pages: Then the system breaks up each positive training page into the minimal elements which can be a part of filtering rules.
Training examples for RI consisting of the following properties are generated. — HTML source code of a region indicated by a user. - A sequence of ancestors of the region in a HTML tree. — Index of raw and column when the region is a cell of a table. S. Yamada ami Y. Nakai / Monitoring Partial Update of Web Pages 45 • Training examples for UC are generated with the difference between old values and updated values in an indicated region. (b) The two kinds of generated examples are independently given to a relational learning system and it learns RI rules and UC rules.
Active Mining by Hiroshi Motoda