Travelled to:1 × Australia
1 × China
1 × France
1 × Germany
1 × Korea
1 × Portugal
1 × Switzerland
2 × USA
Collaborated with:P.S.Yu C.Wu B.Shie P.Fournier-Viger J.Su H.Yeh J.Chang K.W.Lin Y.Lin B.Wang Y.Lin J.Ying C.Huang Y.Kao K.Chen S.Zida J.C.Lin
Talks about:mine (8) util (5) high (4) itemset (3) sequenti (2) pattern (2) tempor (2) effici (2) music (2) rule (2)
Person: Vincent S. Tseng
DBLP: Tseng:Vincent_S=
Contributed to:
2015
20152013
201320122010201020072006Wrote 10 papers:
- KDD-2015-TsengYHKC #detection #framework #named
- FrauDetector: A Graph-Mining-based Framework for Fraudulent Phone Call Detection (VST, JCY, CWH, YK, KTC), pp. 2157–2166.
- MLDM-2015-ZidaFWLT #mining #performance
- Efficient Mining of High-Utility Sequential Rules (SZ, PFV, CWW, JCWL, VST), pp. 157–171.
- KDD-2013-WuLYT #mining #sequence
- Mining high utility episodes in complex event sequences (CWW, YFL, PSY, VST), pp. 536–544.
- SAC-2013-Fournier-VigerT #mining #named
- TNS: mining top-k non-redundant sequential rules (PFV, VST), pp. 164–166.
- KDD-2012-WuSTY #mining
- Mining top-K high utility itemsets (CWW, BES, VST, PSY), pp. 78–86.
- KDD-2010-TsengWSY #algorithm #mining #named #performance
- UP-Growth: an efficient algorithm for high utility itemset mining (VST, CWW, BES, PSY), pp. 253–262.
- SAC-2010-ShieTY #data type #mining #online
- Online mining of temporal maximal utility itemsets from data streams (BES, VST, PSY), pp. 1622–1626.
- SAC-2010-SuYT #music #novel #recommendation
- A novel music recommender by discovering preferable perceptual-patterns from music pieces (JHS, HHY, VST), pp. 1924–1928.
- SAC-2007-TsengSWL #image #visual notation #web
- Web image annotation by fusing visual features and textual information (VST, JHS, BWW, YML), pp. 1056–1060.
- SAC-2006-TsengCL #e-commerce #mining #navigation #personalisation #predict
- Mining and prediction of temporal navigation patterns for personalized services in e-commerce (VST, JCC, KWL), pp. 867–871.