Forthcoming and Online First Articles

International Journal of Knowledge Science and Engineering

International Journal of Knowledge Science and Engineering (IJKSE)

Forthcoming articles have been peer-reviewed and accepted for publication but are pending final changes, are not yet published and may not appear here in their final order of publication until they are assigned to issues. Therefore, the content conforms to our standards but the presentation (e.g. typesetting and proof-reading) is not necessarily up to the Inderscience standard. Additionally, titles, authors, abstracts and keywords may change before publication. Articles will not be published until the final proofs are validated by their authors.

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International Journal of Knowledge Science and Engineering (1 paper in press)

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  • Recommendation of the Latest Research Developments Based on Knowledge Graph   Order a copy of this article
    by Yanjuan Zhang, Wei Chen, Lei Zhao 
    Abstract: How to effectively find the latest developments of the research topic that a paper focuses on is a common problem plaguing researchers nowadays. Researchers usually tackle the problem based on the reference list of the given paper or conduct query on digital libraries, which is ineffective and time-consuming due to the limitation of references and exponentially increasing volume of publications. Previous studies have made great contributions in paper recommendation with content-based filtering, collaborative filtering, citation analysis, and knowledge graphs. However, they have not considered semantic relevance among recommended papers, or suffer from sparsity and cold start problems, or only consider single-level citation relationships, or fail to capture high-order relations. To address these problems, we propose a novel paper recommendation method based on knowledge graphs combining author preference, citation relationships, semantic relevance, and attention mechanism. The experimental results based on real datasets demonstrate that our proposed approach outperforms the state-of-art methods.
    Keywords: knowledge graph; citation relationships; attention mechansim; recommender systems.
    DOI: 10.1504/IJKSE.2021.10039113
     

 

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