Mining Partially-Ordered Sequential Rules Common to Multiple Sequences
نویسندگان
چکیده
منابع مشابه
Mining Sequential Rules Common to Several Sequences
We present an algorithm for mining sequential rules common to several sequences, such that rules have to appear within a maximum time span. Experimental results with real-life datasets show that the algorithm can reduce the execution time, memory usage and the number of rules generated by several orders of magnitude compared to previous algorithms.
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Sequential rule mining is an important data mining task used in a wide range of applications. However, current algorithms for discovering sequential rules common to several sequences use very restrictive definitions of sequential rules, which make them unable to recognize that similar rules can describe a same phenomenon. This can have many undesirable effects such as (1) similar rules that are...
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We propose CMRULES, an algorithm for mining sequential rules common to many sequences in sequence databases – not for mining rules appearing frequently in sequences. For this reason, the algorithm does not use a sliding-window approach. Instead, it first finds association rules to prune the search space for items that occur jointly in many sequences. Then it eliminates association rules that do...
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Predicting the next element(s) of a sequence is a research problem with wide applications such as stock market prediction, consumer product recommendation, and web link recommendation. To address this problem, an effective approach is to mine sequential rules from a set of training sequences to then use these rules to make predictions for new sequences. In this paper, we improve on this approac...
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We introduce a new method for ranked set sampling with multiple criteria. The method relaxes the restriction of selecting just one individual variable from each ranked set. Under the new method for ranking, units are ranked in sets based on linear extensions in partially order set theory with considering all variables simultaneously. Results willbe evaluated by a relatively extensive simulation...
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ژورنال
عنوان ژورنال: IEEE Transactions on Knowledge and Data Engineering
سال: 2015
ISSN: 1041-4347
DOI: 10.1109/tkde.2015.2405509