[PDF] Top 20 Distributional semantic models for the evaluation of disordered language

... The automated methods presented here for rank- ing and filtering words according to their distribu- tions in different corpora, which are adapted from techniques originally developed for topic modeling in the context of ... See full document

... the evaluation of Distributional Semantic Models ...several semantic relations between word pairs (in- cluding hypernymy, synonymy, antonymy, ...word semantic field, ... See full document

... The semantic annotation efforts mentioned so far have been done by experts. Interestingly, crowdsourcing services have proved to be useful for textual entailment annotation. Snow et al. (2008) show high agreement ... See full document

... quantitative evaluation for DSMs using an internal gold standard and re- quiring no external ...on semantic representa- tions extracted from a Wikipedia corpus using one of the most commonly used ... See full document

... • Index of distributional relatedness (rel.index). Given two words a and b represented in a DSM, we consider two alternative ways of quantify- ing the degree of relatedness between a and b. The first option (and ... See full document

... This evaluation is made pos- sible by our extension to all target composition models of the corpus-extracted phrase approxima- tion method originally proposed in ad-hoc settings by Baroni and Zamparelli ... See full document

... The influence of the window size on the accuracy of both DSMs is illustrated in Figure 1. This figure shows that for the three paradigmatic relations (QSYN, ANTI, and HYP), the optimal window size is small, i.e. 1-3 ... See full document

... count models on word similarity and categorization tasks when models were trained on small corpora and with their default post-processing setting (Asr et ... See full document

... using distributional semantic models to identify fine-grained entities and their relations in an online search ...of distributional, syntactic, and rela- tional ... See full document

... Distributional models of lexical semantics have re- cently attracted considerable interest in the NLP ...of evaluation is becoming more ...of evaluation procedures (intrinsic evaluations) ... See full document

... promise: Semantic relations are not limited to tax- onomic types and also include attributes and events strongly related to a concept, but in these cases we have resorted to underspecification, rather than com- ... See full document

... dictive models developed in the field of distribu- tional ...training distributional models of language using machine learning allow for robust representations of nat- ural language ... See full document

... Compositional distributional semantic models (CDSMs) provide a compact model of composi- tionality that produces vector representations of phrases while avoiding the sparsity and storage issues ... See full document

... simplification that we should not apply without being aware of its consequences: there is no ’appropriate number’ of dimensions in natural language, because natural language follows a scale-free ... See full document

... automatic evaluation obtained with the Asiya toolkit (Gonz´alez et ...the evaluation of the Docent baseline sys- tem working with the baseline Moses output as first ...the evaluation of our extensions ... See full document

... decade, distributional seman- tics has been an active area of research to address the problem of understanding the semantics of words in natural ...the distributional se- mantic approach is that the ... See full document

... estimating semantic similarity between ...the distributional hypothesis of meaning (Harris, 1954) assuming that semantic similarity between words is a function of the overlap of their linguistic ... See full document

... Distributional Semantic Models (DSMs) have be- come a staple in natural language ...cessing models — matrix-based models, neural net- works, and hashing methods — have also ... See full document

... The main finding of this work is that the network ap- proach is an appropriate representation and integration framework for textual and visual features. This was ver- ified for the problem of word semantic ... See full document

... on Semantic types and Semantic Groups. The evaluation performed indicates high precision for the neural language models, which in turn hints at the plausible acquisition of relevant ... See full document