A Learning Criterion for Stochastic Rules
Machine Learning - Computational learning theory
C4.5: programs for machine learning
C4.5: programs for machine learning
Stochastic complexity in learning
Journal of Computer and System Sciences - Special issue: 26th annual ACM symposium on the theory of computing & STOC'94, May 23–25, 1994, and second annual Europe an conference on computational learning theory (EuroCOLT'95), March 13–15, 1995
Monitoring a newsfeed for hot topics
KDD '99 Proceedings of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining
Extracting significant time varying features from text
Proceedings of the eighth international conference on Information and knowledge management
Mining from open answers in questionnaire data
Proceedings of the seventh ACM SIGKDD international conference on Knowledge discovery and data mining
Text classification using ESC-based stochastic decision lists
Information Processing and Management: an International Journal
Fast Algorithms for Mining Association Rules in Large Databases
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
Mining product reputations on the Web
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
Topic analysis using a finite mixture model
EMNLP '00 Proceedings of the 2000 Joint SIGDAT conference on Empirical methods in natural language processing and very large corpora: held in conjunction with the 38th Annual Meeting of the Association for Computational Linguistics - Volume 13
Fisher information and stochastic complexity
IEEE Transactions on Information Theory
A decision-theoretic extension of stochastic complexity and its applications to learning
IEEE Transactions on Information Theory
Assessment of the Requirements Management Process using a Two-Stage Questionnaire
QSIC '04 Proceedings of the Quality Software, Fourth International Conference
Key semantics extraction by dependency tree mining
Proceedings of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining
Proceedings of the 11th international conference on Intelligent user interfaces
FACT-Graph: Trend Visualization by Frequency and Co-occurrence
KI '08 Proceedings of the 31st annual German conference on Advances in Artificial Intelligence
Mining fuzzy association rules from questionnaire data
Knowledge-Based Systems
Loopo: Integrated Text Miner for FACT-Graph-Based Trend Analysis
Proceedings of the Symposium on Human Interface 2009 on Human Interface and the Management of Information. Information and Interaction. Part II: Held as part of HCI International 2009
Multiple correspondence analysis for "tall" data sets
Intelligent Data Analysis
Development and case study of trend analysis software based on FACT-Graph
Artificial Life and Robotics
An investigation concerning the generation of text summarisation classifiers using secondary data
MLDM'11 Proceedings of the 7th international conference on Machine learning and data mining in pattern recognition
Knowledge element extraction for knowledge-based learning resources organization
ICWL'07 Proceedings of the 6th international conference on Advances in web based learning
A semi-automated approach to building text summarisation classifiers
MLDM'12 Proceedings of the 8th international conference on Machine Learning and Data Mining in Pattern Recognition
EuroSPI'07 Proceedings of the 14th European conference on Software Process Improvement
Dealing with open-answer questions in a peer-assessment environment
ICWL'12 Proceedings of the 11th international conference on Advances in Web-Based Learning
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Surveys are an important part of marketing and customer relationship management,and open answers (answers to open questions) in particular could contain valuableinformation and provide an important basis for making business decisions. The authors havedeveloped a text mining system that provides a new way of analyzing open answers inquestionnaire data. The product can perform the following two functions: accurateextraction of characteristics for individual analysis targets and accurate extraction ofthe relationships among characteristics of analysis targets. In this article, theydescribe how their text mining system works. It has already been put to use by severallarge corporations in Japan, providing answers to questions about brand images, companyimages, complaints about products, comments written on home pages, business reports, andhelp desk records. In this it has been found to be useful in forming a basis for effectivebusiness decisions.