Word Sense Disambiguation and Human Intuition for Semantic Classification on Homonyms

PACLIC 20 / Wuhan, China / 1-3 November, 200

unsupervised named entity recognition using syntactic and semantic contextual evidence

Proper nouns form an open class, making the incompleteness of manually or automatically learned classification rules an obvious problem. The purpose of this paper is twofold: first, to suggest the use of a complementary "backup" method to increase the robustness of any hand-crafted or machine-learning-based NE tagger; and second, to explore the effectiveness of using more fine-grained evidence—namely, syntactic and semantic contextual knowledge—in classifying NEs

Disambiguierung deutschsprachiger Diskursmarker: Eine Pilot-Studie

Discourse markers such as German aber, wohl or obwohl can be regarded as valuable information for a wide range of text-linguistic applications, since they provide important cues for the interpretation of texts or text segments. Unfortunately, many of them are highly ambiguous. Thus, for their use in applications like automatic text summarizations a reliable disambiguation of discourse markers is needed. This should be done automatically, since manual disambiguation is feasible only for small amounts of data. The aim of this pilot study, therefore, was to investigate methodological requirements of automatic disambiguation of German discourse markers. Two different methods known from word-sense disambiguation, Naive-Bayes and decisionlists, were used for the highly ambiguous marker wenn. A statistical approach was taken to compare the two approaches and different feature combinations

Consumers’ Attitude toward Insurance Companies: A Sentiment Analysis of Online Consumer Reviews

This study considers consumer online reviews for auto, home, and life insurance services to provide insights regarding understanding consumers’ attitude toward different insurance types. We apply the sentiment analysis technique to analyze the overall sentiment of each insurance type since 2012. Our findings show that since 2013 consumers had more negative attitudes toward insurance services. We also extracted consumers’ emotions for each insurance type and found that consumers generally have more negative emotions than positive ones toward insurance services. Moreover, the results show that consumer reviews sentiments could accurately predict consumer review ratings and there are significant differences in review ratings between positive, neutral, and negative consumer reviews sentiments for all insurance types. The results of this study highlight the importance of sentiment analysis in understanding consumers’ opinion toward different services that could help companies to reduce consumers negative attitudes and to attract more customers

A Proposal for word sense disambiguation using conceptual distance

This paper presents a method for the resolution of lexical ambiguity and its automatic evaluation over the Brown Corpus. The method relies on the use of the wide-coverage noun taxonomy of WordNet and the notion of conceptual distance among concepts, captured by a Conceptual Density formula developed for this purpose. This fully automatic method requires no hand coding of lexical entries, hand tagging of text nor any kind of training process. The results of the experiment have been automatically evaluated against SemCor, the sense-tagged version of the Brown Corpus.Postprint (published version

Desambiguisation des sens des mots et representation lexicale du monde

Wiesław Banyś discussed the natural polysemy of the lexicon of natural languages, perceived as one of the major problems of the automatic translation. He also presented a solution for the problem of disambiguation of ambiguous expressions - it pivots on the object-oriented description, enriched with a transfer of various possible translations in a target language to the possible ambiguity of a source language. Finally, the author showed differences in the representations of the world in Polish and French, on the example of some Polish renderings of the French verb gagner

Intervening with Interjections: A Comprehensive Approach to Study Ambiguity in Natural Conversations

Ambiguity during communication, in which a linguistic or gestural sign has multiple meanings, is often considered to be a deterrent to successful communicative interactions. The resolution of ambiguity, therefore, has been a concern in linguistics and in communication studies. This paper critiques certain prevalent experimental paradigms, which have been the most popular approaches to investigate ambiguity resolution, and proposes an alternative methodology to understand and address this phenomenon