Active mining: new directions of data mining by Hiroshi Motoda
By Hiroshi Motoda
The necessity for accumulating proper facts assets, mining priceless wisdom from various types of info resources and briskly reacting to scenario swap is ever expanding. lively mining is a suite of actions each one fixing part of this want, yet jointly reaching the mining aim in the course of the spiral impact of those interleaving 3 steps. This publication is a joint attempt from best and lively researchers in Japan with a subject approximately energetic mining and a well timed file at the leading edge of knowledge assortment, user-centered mining and person interaction/reaction. It deals a latest review of contemporary recommendations with real-world functions, stocks hard-learned stories, and sheds mild on destiny improvement of energetic mining.
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Using Eq. (5) does not only activate the antibody by recognizing other antibodies or antigens, but also suppresses the antibody if the influence by other objects is too strong. The characteristics of immune systems such as immune response and tolerance1 can be explained by the model[l, 7, 10]. The dynamics and the stability of the immune network model have been analyzed by fixing the structure or the topology of the network[l, 7, 10]. As the structure of the keyword network that is generated in the proposed method is defined based on the occurrence of keywords in a set of documents, the analysis noted above cannot be applicable.
Importance of wi, = (average occurrence i n T ) x ( t h e number of texts in which w, occurs 4. Select the literal which has the maximum importance and is not included in a query. Backtracking and iterative literal making process are main difference from the algorithm in FOIL. They are very specific and empirical procedure. Without these extensions. however, many useless rules would be generated. 4 Experiments and Results To evaluate the effectiveness of filtering rules, we conducted retrieval experiments.
We can see the rules directly, thus we find useful patterns or keywords to retrieve relevant pages. Once rules are constructed, the system starts to collect new relevant pages, and display their titles in title view. If the user clicks a title, a browser rises and shows the clicked page. 3 Results Figure 6 shows the relation between judged pages and relevant pages found in the judged pages. The number of relevant pages is average value of 20 topics. About first 10 pages, there is no difference because both retrieval returns the same pages.