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Many PhDs start with a quote from a scientist/author/bearded man from centuries ago. This well-chosen quote demonstrates both the timeless nature of the important topic in question and precisely how...
The current electroencephalography study investigated the relationship between the motor and (language) comprehension systems by simultaneously measuring mu and N400 effects. Specifically, we examined...
This article presents a new model for word sense disambiguation formulated in terms of evolutionary game theory, where each word to be disambiguated is represented as a node on a graph whose edges r...
Hashtags are creative labels used in micro-blogs to characterize the topic of a message/discussion. Regardless of the use for which they were originally intended, hashtags cannot be used as a means ...
Word sense disambiguation and the related field of automated word sense induction traditionally assume that the occurrences of a lemma can be partitioned into senses. But this seems to be a much eas...
Information-theoretic measures are among the most standard techniques for evaluation of clustering methods including word sense induction (WSI) systems. Such measures rely on sample-based estimates of...
Word Sense Disambiguation (WSD) systems automatically choose the intended meaning of a word in context. In this article we present a WSD algorithm based on random walks over large Lexical Knowledge ...
The evaluation of several tasks in lexical semantics is often limited by the lack of large amounts of manual annotations, not only for training purposes, but also for testing purposes. Word Sense Disa...
Web search result clustering aims to facilitate information search on the Web. Rather than the results of a query being presented as a flat list, they are grouped on the basis of their similarity and ...
We introduce a generative probabilistic model, the noisy channel model, for unsupervised word sense disambiguation. In our model, each context C is modeled as a distinct channel through which the sp...
The task of annotating texts with senses from a computational lexicon is widely recognized to be complex and often subjective. Although strategies like interannotator agreement and voting can be app...
Word sense disambiguation (WSD) is a computational linguistics task likely to benefit from the tradition of combining different knowledge sources in artificial intelligence research. An i...
Making Sense of Nonce Sense     Making Sense  Nonce Sense       2015/6/25
A 'parser' is a device, either human or mechanical, that is designed to analyse a person's utterances as a part of deciding what that person meant. Most mechanical parsers do this by breaking down, or...
This paper discusses ensembles of simple but heterogeneous classifiers for word-sense disambiguation, examining the Stanford-CS224N system entered in the SENSEVAL-2 English lexical sample task. First-...
We propose a general model for joint inference in correlated natural language processing tasks when fully annotated training data is not available, and apply this model to the dual tasks of word sense...

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