WN is an on-line lexical reference system whose design is inspired by current psycholinguistic theories of human lexical memory. Nouns, verbs, adjectives and adverbs are organised into synonym sets, each representing one underlying lexical concept. Different kinds of semantic relations link the synonym sets (synsets). WN is based on word meaning; all of the words that can express a given sense ...

Besides synsets and semantic relations, synset glosses are an important feature of wordnets. However, due to the required effort, their creation is sometimes left undone. This happens in Onto.PT, a Portuguese wordnet created automatically, which does not have glosses. In our work, we exploited Portuguese dictionaries to automatically assign definitions to the synsets of Onto.PT. For this purpos...

The proposed approach deals with the detection of jargon words in electronic data in different communication mediums like internet, mobile services etc. But in the real life, the jargon words are not used in complete word forms always. Most of the times, those words are used in different abbreviated forms like sounds alike forms, taboo morphemes etc. This proposed approach detects those abbrevi...

We present AutoExtend, a system to learn embeddings for synsets and lexemes. It is flexible in that it can take any word embeddings as input and does not need an additional training corpus. The synset/lexeme embeddings obtained live in the same vector space as the word embeddings. A sparse tensor formalization guarantees efficiency and parallelizability. We use WordNet as a lexical resource, bu...

We present in this paper a series of induced methods to assign domain tags to WordNet entries. Our prime objective is to enrich the contextual information in WordNet specific to each synset entry. By using the available lexical sources such as Far East Dictionary and the contextual information in WordNet itself, we can find a foundation upon which we can base our categorization. Next we further...

In this paper, a new method for English-Chinese cross-lingual information retrieval is proposed and evaluated in NTCIR-II project. We use the bilingual resources and contextual information to deal with the word sense disambiguation (WSD) and translation disambiguation for query translation. An EnglishChinese WordNet and a synset co-occurrence model are adopted to solve the problem of word sense...

CoreNet, which is built on 2,937 semantic categories, is a multilingual lexico-semantic network aiming at bridging multiple languages/parts-of-speech for a variety of NLP applications. To foster its more widespread use, we have attempted to link semantic categories of CoreNet to Princeton WordNet. To ameliorate translation problems between CoreNet (mostly written in Korean) and English WordNet ...

Having in mind the automatic acquisition and integration of knowledge from different heterogeneous resources, this paper proposes several automatic methods for attaching term-based relational triples to the synsets of a thesaurus, without exploiting the extraction context for disambiguation. After using the proposed methods to attach triples, extracted from a Portuguese dictionary, to the synse...

Increasing and varied applications of wordnets call for the creation of methods to evaluate their quality. However, no such comprehensive methods to rate and compare wordnets exist. We begin our search for wordnet evaluation strategies by attempting to validate synsets. As synonymy forms the basis of synsets, we present an algorithm based on dictionary definitions to verify that the words prese...

The new trend in sentiment classification is to use semantic features for representation of documents. We propose a semantic space based on WordNet senses for a supervised document-level sentiment classifier. Not only does this show a better performance for sentiment classification, it also opens opportunities for building a robust sentiment classifier. We examine the possibility of using simil...