A SURVEY ON ERGODIC RATING PREDICTION USING SEQUENCE CLASSIFICATION
Journal Title: Elysium Journal of Engineering Research and Management - Year 2016, Vol 4, Issue 6
Abstract
Sequence classification has an extensive of applications range such as analysis of the genome, retrieval of information, information about fitness, economics, and abnormal detection. Thus, it creates sequence classification, a more interesting task while the current methods only emphasis of frequency on the concept but not over the time. There exist many more algorithms for upholding sequential patterns. The older datasets are removed and other datasets get updated. Hence, it is clear that timestamp was an important attribute of each dataset for the process of data mining and it provides more accurate and useful information. Sequential patterns use static databases, as time passes by new datasets are inserted and makes the current databases into the dynamic database enhancing the ergodicity of prediction. A brief review of the contemporary work on sequence classification is presented along with highlighting rating prediction.
Authors and Affiliations
Sundar C, Manjula L
Keywords
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