A layered architecture for probabilistic complex pattern recognition to detect user preferences
作者： Michael Glodek , Thomas Geier , Susanne Biundo , Günther Palm
DOI: 10.1016/J.BICA.2014.06.003
关键词:
摘要: Abstract The recognition of complex patterns is nowadays one the most challenging tasks in machine learning, and it promises to be great benefit for many applications, e.g. by allowing advanced human computer interaction access user’s situative context. This work examines a layered architecture that operates on different temporal granularities infer user preferences. Classical hidden Markov models (HMM), conditioned HMM (CHMM) fuzzy CHMM (FCHMM) are compared find best configuration lower layers. In uppermost layer, logic network (MLN) applied preference probabilistic rule-based manner. For each layer comprehensive evaluation given. We provide empirical evidence showing using FCHMM MLN well-suited recognize
sci-hub.se 参考文章(21)
Nir Friedman, Daniel L. Koller, Probabilistic graphical models : principles and techniques The MIT Press. ,(2009)
Aniruddha Kembhavi, Tom Yeh, Larry S. Davis, Why did the person cross the road (there)? scene understanding using probabilistic logic models and common sense reasoning european conference on computer vision. pp. 693- 706 ,(2010) , 10.1007/978-3-642-15552-9_50
Michael Glodek, Friedhelm Schwenker, Günther Palm, Detecting actions by integrating sequential symbolic and sub-symbolic information in human activity recognition machine learning and data mining in pattern recognition. pp. 394- 404 ,(2012) , 10.1007/978-3-642-31537-4_31
Christopher M. Bishop, Pattern Recognition and Machine Learning ,(2006)
Son D. Tran, Larry S. Davis, Event Modeling and Recognition Using Markov Logic Networks Lecture Notes in Computer Science. pp. 610- 623 ,(2008) , 10.1007/978-3-540-88688-4_45
Stefan Scherer, Michael Glodek, Friedhelm Schwenker, Nick Campbell, Günther Palm, Spotting laughter in natural multiparty conversations ACM Transactions on Interactive Intelligent Systems. ,vol. 2, pp. 1- 31 ,(2012) , 10.1145/2133366.2133370
Matthew Richardson, Pedro Domingos, Markov logic networks Machine Learning. ,vol. 62, pp. 107- 136 ,(2006) , 10.1007/S10994-006-5833-1
S. Wrede, G. Sagerer, J. Fritsch, C. Bauckhage, An XML based framework for cognitive vision architectures international conference on pattern recognition. ,vol. 1, pp. 757- 760 ,(2004) , 10.1109/ICPR.2004.173
ANNE WILSON, JAMES HENDLER, Linking Symbolic and Subsymbolic Computing Connection Science. ,vol. 5, pp. 395- 414 ,(1993) , 10.1080/09540099308915707
Michael Glodek, Martin Schels, Friedhelm Schwenker, Günther Palm, Combination of sequential class distributions from multiple channels using Markov fusion networks Journal on Multimodal User Interfaces. ,vol. 8, pp. 257- 272 ,(2014) , 10.1007/S12193-014-0149-0