Semantic Polarity of Adjectival Predicates in Online Reviews

Web users produce more and more documents expressing opinions. Because these have become important resources for customers and manufacturers, many have focused on them. Opinions are often expressed through adjectives with positive or negative semantic values. In extracting information from users' opinion in online reviews, exact recognition of the semantic polarity of adjectives is one of the most important requirements. Since adjectives have different semantic orientations according to contexts, it is not satisfying to extract opinion information without considering the semantic and lexical relations between the adjectives and the feature nouns appropriate to a given domain. In this paper, we present a classification of adjectives by polarity, and we analyze adjectives that are undetermined in the absence of contexts. Our research should be useful for accurately predicting semantic orientations of opinion sentences, and should be taken into account before relying on an automatic methods.

Morphological annotation of Korean with Directly Maintainable Resources

This article describes an exclusively resource-based method of morphological annotation of written Korean text. Korean is an agglutinative language. Our annotator is designed to process text before the operation of a syntactic parser. In its present state, it annotates one-stem words only. The output is a graph of morphemes annotated with accurate linguistic information. The granularity of the tagset is 3 to 5 times higher than usual tagsets. A comparison with a reference annotated corpus showed that it achieves 89% recall without any corpus training. The language resources used by the system are lexicons of stems, transducers of suffixes and transducers of generation of allomorphs. All can be easily updated, which allows users to control the evolution of the performances of the system. It has been claimed that morphological annotation of Korean text could only be performed by a morphological analysis module accessing a lexicon of morphemes. We show that it can also be performed directly with a lexicon of words and without applying morphological rules at annotation time, which speeds up annotation to 1,210 word/s. The lexicon of words is obtained from the maintainable language resources through a fully automated compilation process.