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ACL 2010 GEMS Workshop on "GEometrical Models of natural language Semantics"

GEMS 2010

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Important: GEMS 2010 is running a double-blind review process. In preparing your manuscript, do not include any information which could reveal your identity, or that of your co-authors. The title section of your manuscript should not contain any author names, email addresses, or affiliation status. If you do include any author names on the title page, your submission will be automatically rejected. In the body of your submission, you should eliminate all direct references to your own previous work. That is, avoid phrases such as "this contribution generalizes our results for XYZ". Also, please do not disproportionately cite your own previous work. In other words, make your submission as anonymous as possible. We need your cooperation in our effort to maintain a fair, double-blind reviewing process - and to consider all submissions equally.

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Unsupervised Learning through document-based, collocational and syntagmatic spaces
Supervised Learning and Word Spaces
From Unsupervised to Semi-supervised Learning
Eigenvector methods and Geometrical Embeddings
Higher order tensors and Quantum Logic extensions
Feature engineering in machine learning models
Computational complexity and evaluation issues
Graph-based models over semantic spaces
Logic and inference in semantic spaces
Psychological and cognitive theories of semantic spaces Applications in the humanities and social sciences
Large-scale implementations of distributional models
Applications and impact on Web search, Web mining, Query log mining, etc.
Word sense disambiguation and discrimination
Induction of Selectional preferences
Acquisition of lexicons and linguistic patterns
Conceptual clustering
Kernels methods for NLP
Modeling of linguistic theories and ontological knowledge
Manifold learning for NLP
Transfer learning for NLP
Quantitative extensions of Formal Concept Analysis
Question Answering
Textual Entailment
 
 

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