Equivalent Entity Mining Commencing On Relative Uncertainty

Abstract

Contrast entities are an significant part of decision making progression. To assist judgment making it is useful to evaluate entities that share widespread utility but have distinguishing peripheral characteristics. One possible slant is comparable entity mining from comparative uncertainty. The method used is weakly supervised bootstrapping tactic which identifies the relative question and take out the comparable entity. This is done by distinguish whether a particular question is comparative or not. A sequential prototype is generated and is called an indicative extraction pattern (IEP) if it can be worn to identify comparative questions and dig up comparator pairs with soaring reliability. This technique achieves the F1-measure of 82.5 percent in comparative question credentials and 83.3 percent in comparable entity mining. Inwards proposed system Clique grow examination is used in which the comparable associations are extended and it is used to control assorted query logs from users. Ranking system is used to rank the comparable entities for user input ingress and the results show substantially relevance to user’s similarity intent.

Authors and Affiliations

sangeetha k, dharmajee rao d. t. v

Keywords

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  • EP ID EP28189
  • DOI -
  • Views 273
  • Downloads 2

How To Cite

sangeetha k, dharmajee rao d. t. v (2015). Equivalent Entity Mining Commencing On Relative Uncertainty. International Journal of Research in Computer and Communication Technology, 4(4), -. https://europub.co.uk/articles/-A-28189