A Multi-criteria Collaborative Filtering Approach for Research Paper Recommendation in Papyres
A Multi-criteria Collaborative Filtering Approach for Research Paper Recommendation in Papyres
复制标题
纸莎草研究论文推荐的多标准协同过滤方法
DOI：
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发表时间：
2009
期刊：
影响因子：
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通讯作者：
Esma Aïmeur
中科院分区：
文献类型：
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作者：
Amine Naak;H. Hage;Esma Aïmeur
研究生，教授和研究人员定期访问，审查和使用大量的文献。在以前的工作中，我们提出了Papyres，一个研究论文管理系统，它结合了书目功能沿着与论文推荐技术和文档管理工具，以提供一套功能来定位研究论文，处理和维护的书目，并管理和共享知识的研究文献。在这项工作中，我们详细介绍Papyres的论文推荐技术。具体来说，Papyres采用了一种混合推荐系统，该系统结合了基于内容的过滤和协作过滤，以帮助研究人员找到研究材料。特别是，在这项工作中特别注意的是给予协同过滤过程中，一个多标准的方法是用来评估的文章，让研究人员表示他们的兴趣，在特定部分的文章。此外，我们提出，测试和比较几种方法来确定在协同过滤过程中的邻居，如提高推荐的准确性。
Graduate students, professors and researchers regularly access, review, and use large amounts of literature. In previous work, we presented Papyres, a Research Paper Management Systems, which combines bibliography functionalities along with paper recommender techniques and document management tools, in order to provide a set of functionalities to locate research papers, handle and maintain the bibliographies, and to manage and share knowledge about the research literature. In this work we detail Papyres’ paper recommendation technique. Specifically, Papyres employs a Hybrid recommender system that combines both Content-based and Collaborative filtering to help researchers locate research material. Particularly, in this work special attention is given to the Collaborative filtering process, were a multi-criteria approach is used to evaluate the articles, allowing researchers to denote their interest in specific parts of articles. Moreover, we propose, test and compare several approaches to determine the neighbourhood in the Collaborative filtering process such as to increase the accuracy of the recommendation.