This paper presents a method for automatic classification of semantic relations between nominals using Sequential Minimal Optimization. We participated in the four categories of SEMEVAL task 4 (A: No Query, No Wordnet; B: WordNet, No Query; C: Query, No WordNet; D: WordNet and Query) and for all training datasets. Best scores were achieved in category B using a set of feature vectors including ...

We bootstrapped Chinese WordNet with semantic domain labels of WordNet Domains for constructing a language resource called Chinese WordNet Domains. The bootstrapping methods work from three aspects: 1) Princeton WordNet alignment, 2) lexical semantic relations and 3) domain taxonomy mapping. Experimental results of our proposed bootstrapping based domain predication achieve satisfying effects. ...

The present study describes recent developments of Chinese Wordnet, which has been reformatted using the lemon model and published as part of the Linguistic Linked Open Data Cloud. While lemon suffices for modeling most of the structures in Chinese Wordnet at the lexical level, the model does not allow for finergrained distinction of a word sense, or meaning facets, a linguistic feature also at...

The “basic level”, according to experiments in cognitive psychology, is the level of abstraction a hierarchy concepts at which humans perform tasks quicker and with greater accuracy than other levels. We argue that applications use concept hierarchies could improve their user interfaces if they ‘knew’ are basic concepts. This paper examines what extent can be learned from data. test utility thr...

Introduction A Swedish version of WordNet was created and around 300 Swedish adjectives, mainly from the semantic field of strength, were implemented. This paper is a documentation of the implementation. The purpose of the study was to investigate the possibilities of applying WordNet to Swedish and to illuminate general problems with WordNet as well as specific problems in the handling of adje...

WordNet is a crucial resource that aids in several Natural Language Processing (NLP) tasks. The WordNet development activity for 18 Indian languages has been initiated in INDIA by the IndoWordNet1 consortium using the expansion approach with the Hindi WordNet developed by IIT Bombay, as the source. After linking 20K synsets, it was decided that each of these languages should find the coverage o...