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 Conference Papers (Available on Advance Programs)  (Sort by: Date Descending)
 Results 1 - 6 of 6  /   
Committee Date Time Place Paper Title / Authors Abstract Paper #
R 2023-11-03
13:55		 Ishikawa The Kanazawa Chamber of Commerce and Industry
(Primary: On-site, Secondary: Online)		 A Study on Preventive Maintenance Policy under Limited Information about Failure Time
Yasuhiko Takemoto (KINDAI Univ.), Ikuo Arizono (Okayama Univ.) R2023-45		 In the traditional mathematical model about preventive maintenance, a distribution function about failure time has been ... [more] R2023-45
pp.7-9
NLC, TL 2016-06-04
16:50		 Hokkaido Otaru University of Commerce Identification of Tweets that Mention Books -- Effects of Features, Data Size, and ML Algorithms --
Shuntaro Yada, Kyo Kageura (UTokyo) TL2016-7 NLC2016-7		 We report performances of a classifier that identify Tweets that Mention Books (TMB) from tweets that contain the same s... [more] TL2016-7 NLC2016-7
pp.29-34
NLC 2012-08-30
17:15		 Kanagawa Fuji Xerox Emotion estimation of commentary tweets
Yasuhiro Tajima (OPU) NLC2012-16		 We propose estimation performances about emotion of tweets attached to web news articles.
The estimation mathod is a n... [more]		 NLC2012-16
pp.37-40
PRMU, DE 2007-06-29
10:00		 Hokkaido Hokkaido Univ. Recommendation Method for Improving Customer Lifetime Value
Tomoharu Iwata, Kazumi Saito, Takeshi Yamada (NTT) DE2007-11 PRMU2007-37		 It is important for online stores to improve Customer Lifetime Value (LTV) if they are to increase their profits. Conven... [more] DE2007-11 PRMU2007-37
pp.57-62
AI 2007-05-31
11:10		 Tokyo Kikai-Shinko-Kaikan Bldg. Collaborative Filtering using Purchase Sequences
Tomoharu Iwata, Takeshi Yamada, Naonori Ueda (NTT) AI2007-3		 We propose a collaborative filtering method that uses sequential information in purchase histories for recommendations. ... [more] AI2007-3
pp.13-18
PRMU, NLC 2005-02-24
11:00		 Tokyo   Optimal combination of labeled and unlabeled data for semi-supervised classification
Akinori Fujino, Naonori Ueda, Kazumi Saito (NTT) 		Unlabeled data are used to improve the accuracy of classifiers when the number of labeled data is not enough. In probabi... [more] NLC2004-100 PRMU2004-182
pp.19-24
 Results 1 - 6 of 6  /   
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