Mining Lexical Co-occurrence Features Based Research On Construction Engineering English

The application of Artificial Intelligence techniques on data mining as well as semantic studies has given rise to new discoveries over the research of lexicons in English for Specific Purposes (ESP). The present paper, assisted by the corpus software, carries out a data mining research on the lexical co-occurrence features and explores an empirical study of semantic preferences in Construction Engineering English. The semantic co-occurrence research has been conducted from three aspects involving lexical categories, lexical collocations and lexical colligations. With data retrieval and context analysis, the present research has found out that the lexical categories of Construction Engineering English are limited to seven fields, which are chemical substance, construction materials, structures, positions & measurement, natural environment, living environment and force. Besides, lexicons in different categories demonstrate distinctive semantic preferences and collocation features. And the semantic colligations of Construction Engineering lexicons are majorly neutral in semantic preference, which further proves the neutral and objective characteristics of technology articles.