HYPNER: a hybrid approach for personalised news recommendation
A personalised news recommendation system extracts news set from multiple press releases and presents the recommended news to the user. In an effort to build a better recommender system with high accuracy, this paper proposes a personalised news recommendation framework named Hybrid Personalised NEw...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Institute of Electrical and Electronics Engineers
2020
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| Online Access: | http://psasir.upm.edu.my/id/eprint/89241/ http://psasir.upm.edu.my/id/eprint/89241/1/NEWS.pdf |
| _version_ | 1848860804738187264 |
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| author | Darvishy, Asghar Ibrahim, Hamidah Sidi, Fatimah Mustapha, Aida |
| author_facet | Darvishy, Asghar Ibrahim, Hamidah Sidi, Fatimah Mustapha, Aida |
| author_sort | Darvishy, Asghar |
| building | UPM Institutional Repository |
| collection | Online Access |
| description | A personalised news recommendation system extracts news set from multiple press releases and presents the recommended news to the user. In an effort to build a better recommender system with high accuracy, this paper proposes a personalised news recommendation framework named Hybrid Personalised NEws Recommendation (HYPNER). HYPNER combines both collaborative filtering-based and content-based filtering methods. The proposed framework aims at improving the accuracy of news recommendation by resolving the issues of scalability due to large news corpus, enriching the user's profile, representing the exact properties and characteristics of news items, and recommending diverse set of news items. Validation experiments showed that HYPNER achieved 81.56% improvement in F1 -score and 5.33% in diversity as compared to an existing recommender system, SCENE. |
| first_indexed | 2025-11-15T12:51:04Z |
| format | Article |
| id | upm-89241 |
| institution | Universiti Putra Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T12:51:04Z |
| publishDate | 2020 |
| publisher | Institute of Electrical and Electronics Engineers |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | upm-892412021-09-20T23:31:56Z http://psasir.upm.edu.my/id/eprint/89241/ HYPNER: a hybrid approach for personalised news recommendation Darvishy, Asghar Ibrahim, Hamidah Sidi, Fatimah Mustapha, Aida A personalised news recommendation system extracts news set from multiple press releases and presents the recommended news to the user. In an effort to build a better recommender system with high accuracy, this paper proposes a personalised news recommendation framework named Hybrid Personalised NEws Recommendation (HYPNER). HYPNER combines both collaborative filtering-based and content-based filtering methods. The proposed framework aims at improving the accuracy of news recommendation by resolving the issues of scalability due to large news corpus, enriching the user's profile, representing the exact properties and characteristics of news items, and recommending diverse set of news items. Validation experiments showed that HYPNER achieved 81.56% improvement in F1 -score and 5.33% in diversity as compared to an existing recommender system, SCENE. Institute of Electrical and Electronics Engineers 2020 Article PeerReviewed text en http://psasir.upm.edu.my/id/eprint/89241/1/NEWS.pdf Darvishy, Asghar and Ibrahim, Hamidah and Sidi, Fatimah and Mustapha, Aida (2020) HYPNER: a hybrid approach for personalised news recommendation. IEEE Access, 8. 46877 - 46894. ISSN 2169-3536 https://ieeexplore.ieee.org/document/9026823 10.1109/ACCESS.2020.2978505 |
| spellingShingle | Darvishy, Asghar Ibrahim, Hamidah Sidi, Fatimah Mustapha, Aida HYPNER: a hybrid approach for personalised news recommendation |
| title | HYPNER: a hybrid approach for personalised news recommendation |
| title_full | HYPNER: a hybrid approach for personalised news recommendation |
| title_fullStr | HYPNER: a hybrid approach for personalised news recommendation |
| title_full_unstemmed | HYPNER: a hybrid approach for personalised news recommendation |
| title_short | HYPNER: a hybrid approach for personalised news recommendation |
| title_sort | hypner: a hybrid approach for personalised news recommendation |
| url | http://psasir.upm.edu.my/id/eprint/89241/ http://psasir.upm.edu.my/id/eprint/89241/ http://psasir.upm.edu.my/id/eprint/89241/ http://psasir.upm.edu.my/id/eprint/89241/1/NEWS.pdf |