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Journal: International Journal of Computer Science and Mobile Computing - IJCSMC (Vol.3, No. 1)

Publication Date:

Authors : ;

Page : 465-469

Keywords : Entity mining; Question answering system; Question Answering Challenge (QAC); Machine learning methods such as Support Vector Machines (SVM); Bayesian learning. Sequential rules (CSRs); label sequential rules (LSRs);

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Comparing individual object with one more is a characteristic component of individual assessment making process. Though, it is not forever straightforward to be familiar with what to evaluate and what are the alternating entity to find the exact information retrieval system. In this paper, learning the number of technique that mechanically evaluates the questions and entity designed for mining consumer outcome for information extraction. Several methods have been anticipated in earlier work to solve the problem of entity mining outcomes and none of the work have been studied the accurate foundation of comparable entities, but supervised knowledge technique give an well-organized learning outcomes for comparable entities for different questions and routinely mine equivalent entities as of relative query with the intention of users posted online. In this article we study the difficulty of earlier work query and answering scheme and finish why we preferring equivalent entity mining.

Last modified: 2014-01-30 22:04:38