As the prevalence of social media on the Internet, opinion mining has become an essential
approach to analyzing so many data. Various applications appear in a wide range of …

Abstract Machine learning about language can be improved by supplying it with specific
knowledge and sources of external information. We present here a new version of the linked …

Continuous word representations, trained on large unlabeled corpora are useful for many
natural language processing tasks. Popular models that learn such representations ignore …

Cross-lingual representations of words enable us to reason about word meaning in
multilingual contexts and are a key facilitator of cross-lingual transfer when developing …

Vector space word representations are learned from distributional information of words in
large corpora. Although such statistics are semantically informative, they disregard the …

Artificial Intelligence federates numerous scientific fields in the aim of developing machines
able to assist human operators performing complex treatments---most of which demand high …

Measuring lexical semantic relatedness is an important task in Natural Language
Processing (NLP). It is often a prerequisite to many complex NLP tasks. Despite an …

This paper presents a scalable method for integrating compositional morphological
representations into a vector-based probabilistic language model. Our approach is …

This paper introduces a new task on Multilingual and Cross-lingual SemanticThis paper
introduces a new task on Multilingual and Cross-lingual Semantic Word Similarity which …

Recent years have seen a great deal of work that exploits collaborative, semi-structured
content for Artificial Intelligence (AI) and Natural Language Processing (NLP). This special …