The Mental Lexicon is an interdisciplinary journal that provides international forum for research bears on the issues of representation and processing words in mind brain. We encourage both submission original reviews significant new developments understanding mental lexicon. publishes work includes, but not limited to following: Models Computational models lexical access production Experimenta...

Numerous sentiment analysis applications make usage of a sentiment lexicon. In this paper we present experiments on hybrid sentiment lexicon acquisition. The approach is corpus-based and thus suitable for languages lacking general dictionarybased resources. The approach is a hybrid two-step process that combines semisupervised graph-based algorithms and supervised models. We evaluate the perfor...

Identifying translations in comparable corpora has inspired many studies in bilingual terminology extraction [4, 5]. Projection-based approaches, which are among the most popular ones, rely on a seed bilingual lexicon. Surprisingly, there is no careful analysis of the impact of the size the initial context and coverage of the lexicon. This is precisely the focus of this study. We observe that s...

This paper describes a lexicon-based text normalisation approach for Spanish tweets. We first compare English and Spanish text normalisation, and hypothesise that an approach previously proposed for English can be adapted to Spanish. A corpus-derived normalisation lexicon is built using distributional similarity, and is combined with existing lexicons (e.g., containing Spanish Internet slang). ...

Lexicon-based handwritten text keyword spotting (KWS) has proven to be a very fast and accurate alternative to lexicon-free methods. Nevertheless, since lexicon-based KWS methods rely on a predefined vocabulary, fixed in the training phase, they perform poorly for any query keyword that was not included in it (i.e. out-of-vocabulary keywords). This turns the KWS system useless for that particul...

There exist two main approaches to automatically extract affective orientation: lexicon-based and corpus-based. In this work, we argue that these two methods are compatible and show that combining them can improve the accuracy of emotion classifiers. In particular, we introduce a novel variant of the Label Propagation algorithm that is tailored to distributed word representations, we apply batc...

The coverage of a parser depends mostly on the quality of the underlying grammar and lexicon. The development of a lexicon both complete and accurate is an intricate and demanding task. We introduce a automatic process for detecting missing, incomplete and erroneous entries in a morphological and syntactic lexicon, and for suggesting corrections hypotheses for these entries. The detection of du...

This paper discusses an approach to augmenting a lexicon for knowledge-based machine translation (KBMT) with information derived from WordNet. The Mikrokosmos project at NMSU's Computing Research Laboratory has concentrated on the creation of the Spanish and Japanese lexicons, so the English lexicon is less developed. We investigated using WordNet as a means to automate portions of the English ...

Abstract This research utilizes a lexicon-based sentiment analysis to reveal the emotions conveyed by various news media and analyze differences among media. NRC Affect Intensity Lexicon is utilized; it provides of words in 8 categories emotions. The lexicon modified reflect context news, i.e., COVID-19 pandemic. Tweets are collected from four Indonesia’s three international English-language Ea...