ProUM: Projection-based utility mining on sequence data
نویسندگان
چکیده
منابع مشابه
Parallel tree-projection-based sequence mining algorithms
Discovery of sequential patterns is becoming increasingly useful and essential in many scientific and commercial domains. Enormous sizes of available datasets and possibly large number of mined patterns demand efficient, scalable, and parallel algorithms. Even though a number of algorithms have been developed to efficiently parallelize frequent pattern discovery algorithms that are based on the...
متن کاملFirst International Workshop on Utility-Based Data Mining Workshop Chairs:
Data mining requires certain information—for example, supervised learning requires training data. Some prior research has recognized that this information often does not simply present itself for free, but involves various acquisition costs. In addition, applying the learned models involves costs and benefits. I introduce a general economic setting that includes as special cases the settings of...
متن کاملSecond International Workshop on Utility-Based Data Mining Workshop Chairs
Researchers often use clinical trials to collect the data needed to evaluate some hypothesis, or produce a classifier. During this process, they have to pay the cost of performing each test. Many studies will run a comprehensive battery of tests on each subject, for as many subjects as their budget will allow – i.e., “round robin” (RR). We consider a more general model, where the researcher can...
متن کاملParallel Formulations of Tree-Projection-Based Sequence Mining Algorithm
Discovery of sequential patterns is becoming increasingly useful and essential in many scientific and commercial domains. Enormous sizes of available datasets and possibly large number of mined patterns demand efficient, scalable, and parallel algorithms. Even though a number of algorithms have been developed to efficiently parallelize frequent pattern discovery algorithms that are based on the...
متن کاملParallel Formulations of Tree-Projection Based Sequence Mining Algorithms
Discovery of sequential patterns is becoming increasingly useful and essential in many scientific and commercial domains. Enormous sizes of available datasets and possibly large number of mined patterns demand efficient, scalable, and parallel algorithms. Even though a number of algorithms have been developed to efficiently parallelize frequent pattern discovery algorithms that are based on the...
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ژورنال
عنوان ژورنال: Information Sciences
سال: 2020
ISSN: 0020-0255
DOI: 10.1016/j.ins.2019.10.033