Finding interesting patterns using user expectations

  • Liu B
  • Hsu W
  • Mun L
 et al. 
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One of the major problems in the field of knowledge discovery (or data mining) is the interestingness problem. Past research and applications have found that, in practice, it is all too easy to discover a huge number of patterns in a database. Most of these patterns are actually useless or uninteresting to the user. But due to the huge number of patterns, it is difficult for the user to comprehend them and
to identify those interesting to him/her. To prevent the user from being
overwhelmed by the large number of patterns, techniques are needed to
rank them according to their interestingness. In this paper, we propose
such a technique, called the user-expectation method. In this technique,
the user is first asked to provide his/her expected patterns according
to his/her past knowledge or intuitive feelings. Given these
expectations, the system uses a fuzzy matching technique to match the
discovered patterns against the user's expectations, and then rank the
discovered patterns according to the matching results. A variety of
rankings can be performed for different purposes, such as to confirm the
user's knowledge and to identify unexpected patterns, which are by
definition interesting. The proposed technique is general and

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  • Bing Liu

  • Wynne Hsu

  • Lai Fun Mun

  • Hing Yan Lee

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