Information Search Trail Recommendation Based on Markov Chain Model and Case-based Reasoning

Afeng Wang , Yiming Zhao , Yijin Chen
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引用次数: 0

Abstract

An information search trail recommendation method based on the Markov chain model and case-based reasoning is proposed. A laboratory user experiment was designed to evaluate the proposed method. The experimental results demonstrated that novice searchers have a positive attitude toward the search trail recommendation and a willingness to use the recommendation. Importantly, this study found that the search trail recommendation could effectively improve novice searchers' search performance. This finding is mainly reflected in the diversity of information sources and the integrity of the information content of the search results. The proposed search trail recommendation method extends the application scope of information recommendations and provides insights to improve the organization and management of online information resources.

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基于马尔可夫链模型和案例推理的信息搜索路径推荐
提出了一种基于马尔可夫链模型和案例推理的信息搜索轨迹推荐方法。设计了一个实验室用户实验来评估所提出的方法。实验结果表明,新手搜索者对搜索路径推荐的态度是积极的,并且愿意使用搜索路径推荐。重要的是,本研究发现搜索路径推荐可以有效地提高新手搜索者的搜索性能。这一发现主要体现在信息源的多样性和搜索结果信息内容的完整性。所提出的搜索线索推荐方法扩展了信息推荐的应用范围,为改进在线信息资源的组织和管理提供了见解。
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来源期刊
Data and information management
Data and information management Management Information Systems, Library and Information Sciences
CiteScore
3.70
自引率
0.00%
发文量
0
审稿时长
55 days
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