Improved content recommendation algorithm integrating semantic information

Article Engineering, Environmental

Correlation analysis and text classification of chemical accident cases based on word embedding

Sifeng Jing et al.

Summary: Accident precursors provide valuable clues for risk assessment and risk warning. Text-mining methods based on deep learning have been shown to be effective in extracting information from chemical accident cases. This study developed a text-mining method for chemical accident cases using word embedding and deep learning, which proved to be efficient in extracting useful insights and classifying different types and causes of accidents.

PROCESS SAFETY AND ENVIRONMENTAL PROTECTION (2022)

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Proceedings Paper Computer Science, Artificial Intelligence

CONTENT-BASED RECOMMENDATION USING MACHINE LEARNING

Yifan Tai et al.

Summary: The study introduces a user profile-based recommender system with a three-step profiling method, including purchase item prediction, purchase category prediction, and user rating prediction. Results show that this method outperformed the baseline model on user dataset, providing reasonable recommendations for users. Future considerations include the use of video signal processing techniques to capture users' facial expressions.

2021 IEEE 31ST INTERNATIONAL WORKSHOP ON MACHINE LEARNING FOR SIGNAL PROCESSING (MLSP) (2021)

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Proceedings Paper Computer Science, Information Systems

A novel content-based recommendation approach based on LDA topic modeling for literature recommendation

Dhiraj Vaibhav Bagul et al.

Summary: A novel content-based recommender system utilizing LDA and Jensen-Shannon distance was proposed for literature recommendations. Results showed a precision score of 62.58% on unseen documents, outperforming the standard cosine-similarity approach which achieved only around 48% precision.

PROCEEDINGS OF THE 6TH INTERNATIONAL CONFERENCE ON INVENTIVE COMPUTATION TECHNOLOGIES (ICICT 2021) (2021)

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Article Computer Science, Artificial Intelligence

User trends modeling for a content-based recommender system

Rahimpour Cami Bagher et al.

EXPERT SYSTEMS WITH APPLICATIONS (2017)

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Article Computer Science, Artificial Intelligence

Diversity, Serendipity, Novelty, and Coverage: A Survey and Empirical Analysis of Beyond-Accuracy Objectives in Recommender Systems

Marius Kaminskas et al.

ACM TRANSACTIONS ON INTERACTIVE INTELLIGENT SYSTEMS (2017)

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Article Computer Science, Cybernetics

Educational recommender systems and their application in lifelong learning

Maria-Iuliana Dascalu et al.

BEHAVIOUR & INFORMATION TECHNOLOGY (2016)

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Article Business

An integrated environment for the development of knowledge-based recommender applications

Alexander Felfernig et al.

INTERNATIONAL JOURNAL OF ELECTRONIC COMMERCE (2006)

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Improved content recommendation algorithm integrating semantic information

相关参考文献

Correlation analysis and text classification of chemical accident cases based on word embedding

CONTENT-BASED RECOMMENDATION USING MACHINE LEARNING

A novel content-based recommendation approach based on LDA topic modeling for literature recommendation

User trends modeling for a content-based recommender system

Diversity, Serendipity, Novelty, and Coverage: A Survey and Empirical Analysis of Beyond-Accuracy Objectives in Recommender Systems

Educational recommender systems and their application in lifelong learning

An integrated environment for the development of knowledge-based recommender applications

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