Despite the abundance of research investigating general and academic vocabularies and developing dozens of word lists, few studies have compared academic vocabulary with general service word lists such as conversation vocabulary. Many EAP researchers assume that university students need to know all the words in West’s (1953) General Service List (GSL) as a prerequisite to academic words (e.g., ...

Methods dealing with bilingual lexicon extraction from comparable corpora are often based on word co-occurrence observation and are by essence more effective when using large corpora. In most cases, specialized comparable corpora are of small size, and this particularity has a direct impact on bilingual terminology extraction results. In order to overcome insufficient data coverage and to make ...

In this paper, I propose a novel word sense disambiguation method based on the global co-occurrence information using NMF. When I calculate the dependency relation matrix, the existing method tends to produce very sparse co-occurrence matrix from a small training set. Therefore, the NMF algorithm sometimes does not converge to desired solutions. To obtain a large number of co-occurrence relatio...

The concept of social innovation is increasingly being discussed to pursue sustainable development. New terms and keywords are created cope with new ideas in various contexts. How these developed the current structure knowledge how we can reinterpret semantic networks empirical context primary motivation this paper. rural constructed understand phenomena better future needs. A multi-methods met...

Several recent papers have described how lexical properties of words can be captured by simple measurements of which other words tend to occur close to them. At a practical level, word co-occurrence statistics are used to generate high dimensional vector space representations and appropriate distance metrics are defined on those spaces. The resulting co-occurrence vectors have been used to acco...

Word Sense Induction (WSI) is an unsupervised approach for learning the multiple senses of a word. Graph-based approaches to WSI frequently represent word co-occurrence as a graph and use the statistical properties of the graph to identify the senses. We reinterpret graph-based WSI as community detection, a well studied problem in network science. The relations in the co-occurrence graph give r...

In this paper, choosing highly frequent keywords from core journals in the field of 1992-2013 national knowledge discovery in CNKI database, counting the number of two frequent keywords co-occurrences in the same journal, then constructing the highly frequent keywords matrix, and transforming the highly frequent keywords matrix into a correlation matrix and a dissimilarity matrix, we analyze th...