Evaluating WordNet-based Measures of Lexical Semantic Relatedness
نویسندگان
چکیده
منابع مشابه
Evaluating WordNet-based Measures of Lexical Semantic Relatedness
The quantification of lexical semantic relatedness has many applications in NLP, and many different measures have been proposed. We evaluate five of these measures, all of which use WordNet as their central resource, by comparing their performance in detecting and correcting real-word spelling errors. An information-content–based measure proposed by Jiang and Conrath is found superior to those ...
متن کاملRandom Walk on WordNet to Measure Lexical Semantic Relatedness
The need to determine semantic relatedness or its inverse, semantic distance, between two lexically expressed concepts is a problem that pervades much of natural language processing such as document summarization, information extraction and retrieval, word sense disambiguation and the automatic correction of word errors in text. Standard ways of measuring similarity between two words on a thesa...
متن کاملPerformance Evaluation of WordNet-based Semantic Relatedness Measures for Word Prediction in Conversational Speech
The recognition of conversational speech is a hard problem. Semantic relatedness measures can improve speech recognition performance when using contextual information, as Demetriou [5] has shown. The standard n-gram approach in language modeling for speech recognition cannot cope with long distance dependencies [4]. Therefore J. Bellegarda [2] proposed combining n-gram language models, which ar...
متن کاملCorpus-based Semantic Relatedness for the Construction of Polish WordNet
The construction of a wordnet, a labour-intensive enterprise, can be significantly assisted by automatic grouping of lexical material and discovery of lexical semantic relations. The objective is to ensure high quality of automatically acquired results before they are presented for lexicographers’ approval. We discuss a software tool that suggests synset members using a measure of semantic rela...
متن کاملWordNet-based Semantic Relatedness Measures in Automatic Speech Recognition for Meetings
This paper presents the application of WordNet-based semantic relatedness measures to Automatic Speech Recognition (ASR) in multi-party meetings. Different word-utterance context relatedness measures and utterance-coherence measures are defined and applied to the rescoring of N best lists. No significant improvements in terms of Word-Error-Rate (WER) are achieved compared to a large word-based ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Computational Linguistics
سال: 2006
ISSN: 0891-2017,1530-9312
DOI: 10.1162/coli.2006.32.1.13