Semantic mining on customer survey
Yang Yu, Jiangbo Dang · 2012
Business intelligence aims to support better business decision-making. Customer survey is priceless asset for intelligent business decision-making. However, business analysts usually have to read hundreds of textual comments and tabular data in survey to manually dig out the necessary information to feed business intelligence models and tools. This paper introduces a business intelligence system to solve this problem by extensively utilizing Semantic Web technologies. Ontology based knowledge extraction is the key to extract interesting terms and understand the logic concept of them. All knowledge extracted forms a semantic knowledge base. Flexible user queries and intelligent analysis can be easily issued to the system over the semantic data store through standard protocol. Besides resolving problems in theory, we designed a flexible, intuitive user interaction interface to explain and present the analysis result for business analysts. Through the real usage of this system, it is validated that our system gives good solution for semantic mining on customer survey for business intelligence.