发明名称 System for management of sentiments and methods thereof
摘要 Systems and methods for improved management of sentiments over conventional approaches are disclosed. Supervised approach is used to augment the rule-based approach for classification. Initially, sentiment evaluation is performed by the system using a rule based approach and an interface is provided to the user to give feedback on the correctness of evaluated sentiment. This feedback is used by the sentiment evaluation system to update the set of rule-based and also apply the supervised approach to train the classifier for evaluating complex posts.
申请公布号 US9514496(B2) 申请公布日期 2016.12.06
申请号 US201414199831 申请日期 2014.03.06
申请人 Infosys Limited 发明人 Natarajan Swaminathan;Deepak Krishnamurthy Sai;Teli Prasanna Nagesh;Subbarao Venugopal;Pisipati Radha Krishna
分类号 G06F17/30;G06Q50/00;G06Q10/10;G06Q30/02 主分类号 G06F17/30
代理机构 LeClairRyan, a Professional Corporation 代理人 LeClairRyan, a Professional Corporation
主权项 1. A method for optimizing sentiment classification, the method comprising: performing, by a sentiment management computing device, a classification analysis on a first post received for sentiment evaluation to determine a first sentiment classification; receiving, by the sentiment management computing device, a second sentiment classification related to the first post from at least one user; and updating, by the sentiment management computing device, the classification analysis when the first sentiment classification does not match the second sentiment classification, wherein the updating the sentiment classification analysis comprises: plotting the first post in a multidimensional feature space, wherein each dimension in the multidimensional feature space represents a unique feature corresponding to the first post;performing a neighborhood operation for the first post to identify a pattern space in the multidimensional feature space containing a plurality of posts associated with the first post; andapplying the second sentiment classification to the plurality of posts in the pattern space, wherein the plurality of posts in the pattern space provide updated training data for the classification analysis.
地址 Bangalore IN