[Objective] This paper proposes a framework for small-scale knowledge acquisition and modeling, aiming to more effectively manage the College Students’ deep mentoring work. [Methods] Firstly, we used the LDA to identify topics of collected documents, as well as the phrases describing the topics. Secondly, we used the concept hierarchy analysis to get the relations among these topics. Finally, we encoded ontology of the modeling results for knowledge retrieval. [Results] This study further refined the granularity of topic knowledge on the basis of LDA modeling, which reduced the difficulty of topic modeling and describe their relationship. [Limitations] We did not examine the expanded knowledge base generated by the new depth mentoring documents. [Conclusions] The proposed framework supports the modeling and retrieval of multi granularity knowledge from deep counseling, such as identifying problems, communication methods, and guiding skills.
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