Temporal knowledge graph embedding via sparse transfer matrix

Article Computer Science, Information Systems

SHARE: Designing multiple criteria-based personalized research paper recommendation system

Arpita Chaudhuri et al.

Summary: The extraneous growth of scientific information over the Internet has made it difficult for researchers to find relevant papers among millions of research papers. Existing research paper recommendation systems have limitations in exploiting prominent information of papers and do not consider a sound ranking strategy. This study proposes a systematic hidden attribute-based recommendation engine (SHARE) that utilizes multiple hidden features to provide valuable insights of papers and a novel ranking strategy to retrieve personalized and important papers.

INFORMATION SCIENCES (2022)

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Article Computer Science, Information Systems

An unsupervised semantic text similarity measurement model in resource-limited scenes

Qi Xiao et al.

Summary: Text similarity measurement is crucial in artificial intelligence tasks. However, there is a lack of focus on resource-limited scenarios. This paper proposes a lightweight and semantically rich text similarity measurement model that outperforms other methods, especially in resource-limited scenes.

INFORMATION SCIENCES (2022)

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Article Computer Science, Information Systems

Domain knowledge-enhanced variable selection for biomedical data analysis

Xingyu Wu et al.

Summary: Machine learning has been successful in analyzing biomedical data. However, the lack of samples in the biomedical field poses challenges for traditional variable selection algorithms. This paper proposes a method that utilizes domain knowledge to overcome this issue and demonstrates its effectiveness.

INFORMATION SCIENCES (2022)

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Article Computer Science, Information Systems

IR-Rec: An interpretive rules-guided recommendation over knowledge graph

Jiaying Chen et al.

Summary: This study introduces an interactive rules-guided recommender framework based on knowledge graph, enriching the content of knowledge graph and extracting paths and behavior rules to achieve better recommendation results.

INFORMATION SCIENCES (2021)

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Review Multidisciplinary Sciences

Knowledge graph quality control: A survey

Xiangyu Wang et al.

Summary: This paper aims to fill the research gap on the quality control of knowledge graphs, promote research and applications by providing a comprehensive survey on the six main evaluation dimensions of KG quality, quality control treatments during KG construction, and quality enhancement methods.

FUNDAMENTAL RESEARCH (2021)

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Article Computer Science, Information Systems