Knowledge Extraction: Automatic Classification of Matching Rules

[1]  Support Vector Machine , 2020 .

[2]  Geoffrey E. Hinton,et al.  A Scalable Hierarchical Distributed Language Model , 2008, NIPS.

[3]  Jeffrey Dean,et al.  Distributed Representations of Words and Phrases and their Compositionality , 2013, NIPS.

[4]  Jason Weston,et al.  A unified architecture for natural language processing: deep neural networks with multitask learning , 2008, ICML '08.

[5]  Jeffrey Dean,et al.  Efficient Estimation of Word Representations in Vector Space , 2013, ICLR.

[6]  Mingzhe Wang,et al.  LINE: Large-scale Information Network Embedding , 2015, WWW.

[7]  Oren Barkan,et al.  ITEM2VEC: Neural item embedding for collaborative filtering , 2016, 2016 IEEE 26th International Workshop on Machine Learning for Signal Processing (MLSP).

[8]  Wenwu Zhu,et al.  Structural Deep Network Embedding , 2016, KDD.

[9]  Robert M. McGraw,et al.  Overview of clustering algorithms , 2001, SPIE Defense + Commercial Sensing.

[10]  Steven Skiena,et al.  DeepWalk: online learning of social representations , 2014, KDD.

[11]  Yun Zhu,et al.  Support vector machines and Word2vec for text classification with semantic features , 2015, 2015 IEEE 14th International Conference on Cognitive Informatics & Cognitive Computing (ICCI*CC).

[12]  Jeffrey E. F. Friedl.  Mastering regular expressions - powerful techniques for Perl and other tools , 1997, Powerful techniques for Perl and other tools.

[13]  Xin Rong,et al.  word2vec Parameter Learning Explained , 2014, ArXiv.

[14]  Oren Barkan,et al.  Bayesian Neural Word Embedding , 2016, AAAI.