BKCA, an E-Consultancy System for Studying

摘要

In education organizations, a number of quotidian and duplicated consulting questions for training programs, university regulations. . . make difficulties, inconvenient and time-consuming for consultants. This work proposes a method to suggest answers of similar questions, which may help both students and consultants in orientation. This method includes two main tasks: (i) query generation which extracts key phrases from input questions, (ii) searching which find out most similar questions with their answers and relevant scores using extracted key phrases. For the first task, a check strategy was used to build key phrase candidates and the Na?ve Bayes Classifier was used to select key phrases. The two different approaches were experimented for the second one: (i) Similarity Comparison Searching, and (ii) Sorl Search Engine. The precision of the key phrase extraction is about 69 %. BKCA, an e-consultancy system for SoICT-HUST, was built and experimented with about 46% relevant question-answer pairs for the Similarity Comparison searching approach, and about 39% for the Sorl Search Engine one.