Improving Root Cause Analysis Using Fuzzy Polarity Identification and Conflict Resolution Techniques

Abstract

Identifying the root cause of feedbacks is one of the major functionalities in a marketing system. Increased use of online social networking media has automatically led to a raise in the users expressing their views in these platforms. Analyzing data from such media provides unbiased information regarding any product or service. This article presents a polarity-based root cause identification technique that identifies the root cause of a query presented by the user. The query is presented to all the available data sources, and the information returned is filtered using conflict resolution techniques. The data is then subjected to a fuzzy polarity analyzer that divides the data into groups based on their polarity levels. The data is then cross-referenced with the domain based ontology to identify the root cause.