Word sense disambiguation (WSD) is the ability to identify the meaning of words in context
in a computational manner. WSD is considered an AI-complete problem, that is, a task …

While the biomedical informatics community widely acknowledges the utility of domain
ontologies, there remain many barriers to their effective use. One important requirement of …

A word's sentiment depends on the domain in which it is used. Computational social science
research thus requires sentiment lexicons that are specific to the domains being studied. We …

Research into corpus-based semantics has focused on the development of ad hoc models
that treat single tasks, or sets of closely related tasks, as unrelated challenges to be tackled …

• San Francisco, ad hoc, by and large, Where Eagles Dare, kick the bucket, part of speech, in
step, the Oakland Raiders, trip the light fantastic, telephone box, call (someone) up, take a …

We present a simple yet effective approach for learning word sense embeddings. In contrast
to existing techniques, which either directly learn sense representations from corpora or rely …

A standard approach to Information Retrieval (IR) is to model text as a bag of words.
Alternatively, text can be modelled as a graph, whose vertices represent words, and whose …

An author may have multiple names and multiple authors may share the same name simply
due to name abbreviations, identical names, or name misspellings in publications or …

The rapid advancement in the theoretical understanding of statistical and machine learning
methods for semisupervised learning has made it difficult for nonspecialists to keep up to …

Work on authorship attribution has traditionally focused on long texts. In this work, we tackle
the question of whether the author of a very short text can be successfully identified. We use …