基于交互感知的探索式搜索中资源的推荐方法

Resource Recommendation Method Based on Interactive Perception in Exploratory Search

基于关键词匹配的信息搜索技术日渐成熟,人们期待搜索引擎更加智能,能够根据模糊需求启发用户找到正确的信息,探索式搜索由此出现。已有依据关键词之间的语义关联进行搜索推荐的探索式搜索方式,能够启发用户找到与当前查询相关的其他信息。然而,这种随机式的推荐方式仅适用于用户对不熟悉的领域进行初步了解的应用场景。针对有特定搜索意图的用户,如何有效利用用户提供的信息,让信息推荐以符合认知规律的方式进行,并且能够使计算机智能地理解用户的下一步信息需求的意图是研究的关键。提出一种基于交互感知的信息推荐方法,设定交互的基本规则,便于系统尽快确定模糊用户需求的搜索意图。示例展示这种方式能够对有效交互进行定量分析,并能有效减少用户与系统之间交互的步数。

Information search technology based on keyword matching is becoming more and more mature. Search en-gines are expected to become more intelligent. As a kind of search engine which satisfies the information searching with fuzzy requirements ？ exploratory search comes up. Some existing methods which recommend information based on se-mantic relations among keywords can inspire users to find other information related to the current query. However,this kind of random recommendation can only achieve some application scenarios like users ^ understanding of unfamiliar areas. For users who have a concrete search intention, how to make computers understand their information requirement based on some prior information is the key issue. This paper proposed a method of information recommendation based on user interactive perception, which includes two basic rules of interaction to make system understand users^ fuzzy re-quirements quickly. The example shows that it allows quantitative analysis of effective interactions. And, it can reduce interaction steps between users and systems.