Тарату тезаурусы

In this paper we explore the use of se- lectional preferences for detecting non- compositional verb-object combinations. To characterise the arguments in a given gram- matical relationship we experiment with …...

Unsupervised selection of semantic relations for improving a distributional thesaurus Work about distributional thesauri has shown that the relations in these thesauri are mainly reliable for high frequency words. In …...

AbstractDistributional thesauri have been applied for a variety of tasks involving semantic relatedness. In this paper, we investigate the impact of three parameters: similarity measures, frequency thresholds and association scores. …...

AbstractThis paper introduces a distributional thesaurus and sense clusters computed on the complete Google Syntactic N-grams, which is extracted from Google Books, a very large corpus of digitized books published …...

. In this paper, we address the issue of building and improving a distributional thesaurus. We first show that existing tools from the information retrieval domain can be directly used …...

In this paper, we address the issue of building and improving a distributional thesaurus. We first show that existing tools from the information retrieval domain can be directly used in …...

In this paper we examine the lexical substitu- tion task for the medical domain. We adapt the current best system from the open domain, which trains a single classifier for …...

We present a sentiment classification sys- tem that participated in the SemEval 2014 shared task on sentiment analysis in Twit- ter. Our system expands tokens in a tweet with semantically …...

We present a new unsupervised mecha- nism, which ranks word n-grams accord- ing to their multiwordness. It heavily re- lies on a new uniqueness measure that computes, based on a …...

We explore the impact of adding distri- butional knowledge to a state-of-the-art coreference resolution system. By inte- grating features based on word and context expansions from a distributional thesaurus (DT), …...

AbstractResources such as WordNet are useful for NLP applications, but their manual construction consumes time and personnel, and frequently results in low coverage. One alternative is the automatic construction of …...

AbstractWith the success of word embedding methods in various Natural Language Processing tasks, all the field of distributional semantics has experienced a renewed interest. Beside the famous word2vec, recent studies …...

This paper reports the IIT-TUDA participation in the SemEval 2016 shared Task 5 of Aspect Based Sentiment Analysis (ABSA) for sub- task 1. We describe our system incorporat- ing domain …...

AbstractThis paper reports team IITPB’s participation in the SemEval 2017 Task 5 on ‘Fine-grained sentiment analysis on financial microblogs and news’. We developed 2 systems for the two tracks. One …...

AbstractDistributed representations of words learned from text have proved to be successful in various natural language processing tasks in recent times. While some methods represent words as vectors computed from …...

AbstractDiscriminating lexical relations among distributionally similar words has always been a challenge for natural language processing (NLP) community. In this paper, we investigate whether the network embedding of distributional thesaurus …...