Research Of Graduates’ Employment Recommendation System Based On Semantic

With the vogorous development of the higher education, more and more people get thehigher education opportunities. While at the same time, the college graduates are facing thehuge employment pressure and the societies are paying more attention to the employment ofthe colleges. At present, most of the existed traditional employment website can simplyprovide broad employment information for the graduates but ignoring the employmentpreferences of the students’, which is not conformed to the employment vision of theemployees’ in the age of information explosion. The employment recommendation is theprocess that recommend the suitable employment information for the graduates, which isfocused on the problem that how to find the relatively suitable employment informationthrough an appropriate recommendation algorithm. The ideal employment recommendationsystem is that can accelerates the employment process of the students’, shorten theemployment cycle and also achieve the double-win employment which can meet thegraduates and employers’ demand through the rational and effective recommendedinformation.This paper mainly studies the undergraduates employment recommendation systembased on the semantic web which is introduced into the study. First of all, set up thepreliminary employment information ontology through the web crawler and the Protégétool. Reasoning according to the reasoning machine and the inference rules of the attributesof the initial ontology such as the professionals, job categories, job responsibilities and soon to obtain the final employment information ontology. Then, compare several similaritycalculation methods and choose the Euclidean distance and Jacobi formulas to calculate thesimilarity of the similar employment information, before which allocates the weightingratio of the ten attributes of the ontology. Finally, recommend the employment informationaccording to the similarity results. The experiments show that the recommendationalgorithm adopted in this paper can provide employment recommendation information forthe graduates better and can help the graduates achieve the efficient and fast employment.At last, the paper summarizes the work and puts forward to the latter study.