In order to solve the problems that the users have personal interest preference,the use of ontology effective information is insufficient,the ontology adaptive learning ability is poor and the efficiency of semantic similarity search based on single strategy is low,etc.,we propose a semantic search algorithm which is based on interest degrees and ontology adaptive learning.In this algorithm,firstly,the ontology information sharing content and the closing-to-equilibrium path strategy of information are used to carry out the weighted measurement of ontology semantic similarity,and user' s interest degree preference is calculate as well； Then,according to user personalised preference it carries out the ontology adaptive learning using ontology evaluation model,so as to improve the information sharing degree of ontology knowledge base.Experiment proves that this algorithm has quite high recall and precision rate.%针对用户个人兴趣度偏好、本体有效信息利用不足、本体自适应学习能力差和基于单一策略的语义相似度搜索效率低等问题,提出一种基于兴趣度和本体自适应学习的语义搜索算法.在该算法中,首先利用本体信息共享含量和信息贴近均衡路径策略来进行本体语义相似度加权度量,并对用户的兴趣度进行偏好计算,然后利用本体评价模型,依据用户个性化偏好进行本体自适应学习,从而提高本体知识库的信息共享度.实验证明,该算法具有较高的查全率和查准率.
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