Natural Language Queries over Heterogeneous Linked Data Graphs: A Distributional-Compositional Semantics Approach
Henning agt talk-caise-semnet
Don’t count, predict! A systematic comparison of context-counting vs. context-predicting semantic vectors
Approximate Semantic Matching of Heterogeneous Events
Sentence generation
Im2013vit
IWCS 2015 Proceedings
1 Distributional Semantics: Word Association and Similarity Ido Dagan Including Slides by: Katrin Erk (mostly), Marco Baroni, Alessandro Lenci (BLESS)
Tutorial on neural probabilistic language models Piotr Mirowski, Microsoft Bing London South England NLP Meetup @ UCL April 30, 2014.
Qual Presentation Daniel Khashabi 1. Outline My own line of research Papers: Fast Dropout training, ICML, 2013 Distributional Semantics Beyond.
Detecting compositionality using semantic vector space models based on syntactic context Guillermo Garrido and Anselmo Peñas NLP & IR Group at UNED Madrid,
Distributional Semantics: Word Association and Similarity
