An unsupervised sentiment analysis method is presented to classify user comments on laptops into positive ones and negative ones. The method automatically extracts informative features in testing dataset and labels the sentiment polarity of each feature to make a domainspecific lexicon. The classification accuracy of this lexicon will be compared to that with an existing general sentiment lexic...

This work describes how we used AnCora-Nom, a Spanish nominalization lexicon, to extend NomLex-PT, a lexical resource for Portuguese, originally based on the English NomLex lexicon and fully integrated to OpenWordNet-PT, our freely available Portuguese WordNet. The complete Spanish lexicon, which contains 1,655 entries, was translated to Portuguese and then compared to our previous data. Furthe...

In this paper the role of the lexicon within typical application tasks based on NLP is analysed. A large scale semantic lexicon is studied within the framework of a NLP application. The coverage of the lexicon with respect the target domain and a (semi)automatic tuning approach have been evaluated. The impact of a corpus-driven inductive architecture aiming to compensate lacks in lexical inform...

This paper presents a syntactic lexicon for English that was originally derived from the Oxford Advanced Learner’s Dictionary and the Oxford Dictionary of Current Idiomatic English, and then modified and augmented by hand. There are more than 37,000 syntactic entries from all 8 parts of speech. An X-windows based tool is available for maintaining the lexicon and performing searches. C and Lisp ...

Sentiment classification is a crucial problem in natural language processing and essential to understand user opinions. There are two main approaches solve this problem, one the classified-based method, other lexicon-based method; however, both methods perform not well on long-sequence methods, each method has its advantages disadvantages. This paper introduced new called Lexiconed BERT, which ...