Current context processing method does not support semantic technology very well,this leads to the limits of semantic search in both accuracy and intelligence.In this paper,we propose a BDI-based semantic search approach,it makes semantic description on dynamic context and uses BDI mechanism to optimise search results.The approach integrates user’s query and dynamic contexts with Belief in BDI framework,reasons the context features through products feature semantics and business semantics,and searches objects features as agent’s Desire,finally it calculates the candidate Intention order through MinHash-based semantic similarity.In combination with the requirement of project,we develop the search system of tourism products in environment of open source BDI Agent of JADEX engine,the system is based on the above mentioned semantic search.Through ID3 decision tree the system extracts context features of current itinerary of users to implement the semantic search function.Experiment shows that the search accuracy of the approach improved significantly relative to the search methods only using semantic similarity,it can satisfy the demand of tourism products search.%目前的上下文处理方法对语义技术支持不足，导致语义搜索在精准度和智能化上存在局限。提出一种基于 BDI（Belief-Desire-Intention）的语义搜索方法，对动态上下文进行语义描述，利用 BDI 机制优化搜索结果。该方法将用户查询、动态上下文与BDI 框架的 Belief 融合，通过产品特征语义、业务语义推理上下文特征和搜索目标特征作为 Desire，通过基于 MinHash 的语义相似度计算进行候选 Intention 排序。结合项目需求，在 JADEX 开源 BDI Agent 环境下，开发了基于上述语义搜索的旅游产品搜索系统。该系统通过 ID3决策树提取用户当前行程的上下文特征实现了语义搜索功能，实验表明该方法搜索准确率相比仅使用语义相似度搜索方法明显提高，能够满足旅游产品搜索的要求。
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