Automated Interestingness Measure Selection for Exhibition Recommender Systems
作者： Kok Keong Bong , Matthias Joest , Christoph Quix , Toni Anwar
DOI: 10.1007/978-3-319-05476-6_23
关键词:
摘要: Exhibition guide system contain various information pertaining to exhibitors, products and events that are happening during the exhibitions. The would be more useful if it is augmented with a recommender system. Our recommend users list of interesting exhibitors based on associations mined from web server logs. recommendations ranked Objective Interestingness Measures OIMs quantify interestingness an association. Due data sparsity, some cannot provide distinct values for different rules hamper ranking process. In mobile applications, crucial because low real estate in device screen sizes. We show our able select OIM 50 perform better than regular Support-Confidence OIM. tested using exhibitions held Germany.
springer.com
core.ac.uk
sci-hub.st 参考文章(16)
Philippe Lenca, Stéphane Lallich, Benoît Vaillant, Modeling of the counter-examples and association rules interestingness measures behavior DMIN. pp. 132- 137 ,(2006)
Francesco Bonchi, Claudio Lucchese, Pushing Tougher Constraints in Frequent Pattern Mining Advances in Knowledge Discovery and Data Mining. pp. 114- 124 ,(2005) , 10.1007/11430919_15
Engelbert Mephu Nguifo, Dhouha Grissa, Sylvie Guillaume, Combining Clustering techniques and Formal Concept Analysis to characterize Interestingness Measures arXiv: Information Theory. ,(2010)
Benoît Vaillant, Philippe Lenca, Stéphane Lallich, A Clustering of Interestingness Measures discovery science. pp. 290- 297 ,(2004) , 10.1007/978-3-540-30214-8_23
Shingo Mabu, Xianneng Li, Kaoru Shimada, Huiyu Zhou, Kotaro Hirasawa, Analysis of various interestingness measures in classification rule mining for traffic prediction society of instrument and control engineers of japan. pp. 1969- 1974 ,(2010)
Junjie Wu, Shiwei Zhu, Hui Xiong, Jian Chen, Jianming Zhu, Adapting the Right Measures for Pattern Discovery: A Unified View systems man and cybernetics. ,vol. 42, pp. 1203- 1214 ,(2012) , 10.1109/TSMCB.2012.2188283
Mojdeh Jalali-Heravi, Osmar R. Zaïane, A study on interestingness measures for associative classifiers acm symposium on applied computing. pp. 1039- 1046 ,(2010) , 10.1145/1774088.1774306
Philippe Lenca, Patrick Meyer, Benoît Vaillant, Stéphane Lallich, On selecting interestingness measures for association rules: User oriented description and multiple criteria decision aid European Journal of Operational Research. ,vol. 184, pp. 610- 626 ,(2008) , 10.1016/J.EJOR.2006.10.059
Pang-Ning Tan, Vipin Kumar, Jaideep Srivastava, Selecting the right interestingness measure for association patterns Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining - KDD '02. pp. 32- 41 ,(2002) , 10.1145/775047.775053
Liqiang Geng, Howard J. Hamilton, Interestingness measures for data mining ACM Computing Surveys. ,vol. 38, pp. 9- ,(2006) , 10.1145/1132960.1132963