The nature of statistical learning theory
The nature of statistical learning theory
ACM Computing Surveys (CSUR)
CMAR: Accurate and Efficient Classification Based on Multiple Class-Association Rules
ICDM '01 Proceedings of the 2001 IEEE International Conference on Data Mining
Hierarchical Clustering Algorithms for Document Datasets
Data Mining and Knowledge Discovery
Data Mining: Concepts and Techniques
Data Mining: Concepts and Techniques
Introduction to Data Mining, (First Edition)
Introduction to Data Mining, (First Edition)
Opinion Mining and Sentiment Analysis
Foundations and Trends in Information Retrieval
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Surveys are an easy, important and reliable method to measure the "pulse" of the organization's stake-holders. A survey helps in identifying improvements to current products, services and business processes. With the advent of the Web, it is now easy to conduct large-scale on-line surveys. However, it is a challenge to analyze the responses to derive novel, interesting, actionable insights and to design effective improvement plans. In this paper, we describe a tool called QUEST for analyzing survey responses. QUEST's pre-packaged knowledge containers provide frequently needed analysis of survey responses. Built-in analysis in QUEST varies from summaries, reports and charts to detailed statistical and data mining analysis and optimization. The analytics is designed to answer specific business questions, detect specific types of patterns, extract specific kind of useful and actionable knowledge and automatically suggest optimal improvement plans. We present a real-life case-study where QUEST was used to analyze responses from a real-life employee satisfaction survey in an IT company.