Despite their similar meanings, near-synonyms may have different usages in different contexts. For second language learners, such differences are not easily grasped in practical use. In this paper, we develop a computer-assisted near-synonym learning system for Chinese English-as-aSecond-Language (ESL) learners using two automatic near-synonym choice techniques: pointwise mutual information (PM...

When acquiring synonyms from large corpora, it is important to deal not only with such surface information as the context of the words but also their latent semantics. This paper describes how to utilize a latent semantic model PLSI to acquire synonyms automatically from large corpora. PLSI has been shown to achieve a better performance than conventional methods such as tf·idf and LSI, making i...

Word similarity computing is one of the most important and fundamental task in the field of natural language processing. Most of word similarity methods perform well in synonyms, but not well between words whose similarity is vague. It confronts the challenge of how to overcome this problem. An approach is proposed to compute Chinese word similarity based on hybrid hierarchical structure by How...

One of the most common lexical misuse problems in the second language context concerns near synonyms. Dictionaries and thesauri often overlook the nuances of near synonyms and make reference to near synonyms in providing definitions. The semantic differences and implications of near synonyms are not easily recognized and often fail to be acquired by L2 learners. This study addressed the distinc...

The growing importance of enterprise risk management and the resulting integration efforts put the need for separate IT risk management frameworks in question. In this research we analyse common and distinct elements of the COSO enterprise risk management and ISACA Risk IT frameworks. The analysis affirms the hypothesis that separate IT risk management frameworks are redundant.

We propose a new method for translation acquisition which uses a set of synonyms to acquire translations from comparable corpora. The motivation is that, given a certain query term, it is often possible for a user to specify one or more synonyms. Using the resulting set of query terms has the advantage that we can overcome the problem that a single query term’s context vector does not always re...

Word Sense Disambiguation (WSD) is one of the key issues in natural language processing. Currently, supervised WSD methods are effective ways to solve the ambiguity problem. However, due to lacking of large-scale training data, they cannot achieve satisfactory results. In this paper, we suppose synonyms for context words that can provide more knowledge for WSD task, and present two different WS...

This paper aims to explore how translators translate both the connotative and denotative meanings of near-synonyms from Quran into English language. The article will shed light on phenomenon near-synonymy, as well its translator’s background could have influenced their translation. There has been a dearth attention translation in Quran; accordingly, this study examines three pairs particular tr...

Zipf's law states that if words of language are ranked in the order of decreasing frequency in texts, the frequency of a word is inversely proportional to its rank. It is very reliably observed in the data, but to date it escaped satisfactory theoretical explanation. This article suggests that Zipf's law may result from a hierarchical organization of word meanings over the semantic space, which...