Automatically identifying related specialist terms is a difficult and important task required to understand the lexical structure of language. This paper develops a corpus-based method of extracting coherent clusters of satellite terminology — terms on the edge of the lexicon — using co-occurrence networks of unstructured text. Term clusters are identified by extracting communities in the coocc...

Document clustering is a popular research field in Natural Language Processing, Data Mining and Information Retrieval. The problem of lexical unit (LU) clustering has been less addressed, and even less so the problem of labeling LU clusters. However, in our application that deals with the distillation of relational tuples from patent claims as input to block diagram or a concept map drawing pro...

Connor et al. (2008) mention “specifying textual requirements of genres” (p.12) as one of the reasons which have motivated researchers in the analysis of writing. Members of each genre should be able to produce and retrieve these textual requirements appropriately to be considered communicatively proficient. One of the textual requirements of genres is regularities of specific forms and content...

Objectives: Lexical access is the process by which the basic conceptual, syntactical and morpho-phonological information of words are activated. Most studies of lexical access have focused on picture naming. There is hardly any previous research on other parameters of lexical access such as verbal fluency and analysis of connected speech in Persian normal participants. This study investigates t...

  This paper investigates the use of ‘lexical bundles’ in two broad corpora of journalistic writing. The aim of this study is to compare the use of lexical bundles in the two domains, one consisted of newspaper articles written in English and published in England and the other one comprised of newspaper articles written in Persian from Iranian publications. For this purpose, the frequency...

Keywords are list of significant words or terms that best present the document context in brief and relate to the textual context. Extraction models are categorized into either statistical, linguistic, machine learning or a combination of these approaches. This paper introduces a model for extracting keywords by making words pairs and clustering these pairs based on the Semantic similarity that...

In Moroccan Arabic it is widely accepted that short vowels are mostly elided, resulting in consonant clusters and consonant geminates. In this paper we present evidence from our exploratory timing study that challenges this widely accepted principle. We work with minimal pairs of singleton consonants vs. geminates (e.g. /bka/ vs. /b kka/) that reveals a presence of a vowel insertion between the...

Broad-coverage lexical resources such as WordNet are extremely useful. However, they often include many rare senses while missing domain-specific senses. We present a clustering algorithm called CBC (Clustering By Committee) that automatically discovers concepts from text. It initially discovers a set of tight clusters called committees that are well scattered in the similarity space. The centr...