AffectiveSpace: Blending Common Sense and Affective Knowledge to Perform Emotive Reasoning
By Erik Cambria, Amir Hussain, Catherine Havasi, Chris Eckl. 2009
62 citations recorded by the source corpus.
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
- Yoshua Bengio
- Erik Cambria
- Percy Liang
- Antoine Bordes
- Jason Aaron Edward Weston
- Mohit Bansal
- Kyunghyun Cho
- Soujanya Poria
Citations in the corpus
- A semantic matching energy function for learning with multi-relational data (2013, methodology): “Other directions have also been proposed derived from probabilistic matrix factorization for multi-dimensional data (Chu and Ghahramani 2009) or by adapting dimensionality reduction techniques such as SVD (Speer et al. 2008; Cambria et al. 2009).”
- SenticNet: A Publicly Available Semantic Resource for Opinion Mining (2010, methodology): “AffectiveSpace (Cambria et al. 2009a) is a n -dimensional vector space built from ConceptNet and WordNet-Affect, a linguistic resource for the lexical representation of affective knowledge (Strapparava and Valitutti 2004).”
- A survey on opinion mining and sentiment analysis: Tasks, approaches and applications (2015, background): “AffectiveSpace [141] was able to grasp the semantic and affective similarity between concepts by plotting them into a multi-dimensional vector space.”