A Context-aware Interest Drift Network for Session-based News Recommendations

Meng, Lingkang; Shi, Chongyang

doi:10.1109/iccc51575.2020.9345260

Cited by 2 publications

(2 citation statements)

References 12 publications

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“…For instance, (Li, J et al, 2022) employ a multi-head attention approach to learn user preferences. (Meng, L., & Shi, C., 2020) propose a CalDN model, which through a bidirectional attention recurrent network, it captures various aspects of user reading preferences and provides personalized reading suggestions. (Tran et al, 2023) introduce the CupMar method, utilizing multiple attribute features in the news encoder to obtain rich news representations through neural network layers.…”

Section: Preference-based News Recommendationmentioning

confidence: 99%

“…CalDN (Meng, L., & Shi, C., 2020) captures user reading preferences from various aspects, including the environment, breaking news, and news content information, using a bidirectional attention recurrent network, providing personalized reading recommendations. MINER (Li, J., et al, 2022) employs a multi-attention approach to learn and express user preferences.…”

Section: Baselinesmentioning

confidence: 99%

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A Hotspot-Aware Personalized News Recommendation Mechanism Based on DistilBERT-TC-MA

He,

Wang

2024

International Journal of Distributed Systems and Technologies

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Aiming at the problems of existing news recommendation methods, such as inadequate exploration of the semantic information of news, neglecting potential hotspot features of news, and challenging the balance between user preferences and hotspot features, a hotspot-aware personalized news recommendation model (DistilBERT-TC-MA) is suggested, which integrates the distilled version of BERT (DistilBERT), text convolutional neural network (TextCNN), and multilayer attention (MA). First, it takes full advantage of DistilBERT, TextCNN, and self-attention mechanism to achieve news encoding. Following this, representations of trending news are dynamically aggregated using the attention mechanism, while user preferences are mined utilizing user click history. Finally, in order to successfully accomplish the click prediction of candidate news, the hotspot features, user preferences, and candidate news are ultimately combined using a click predictor. The experimental results of the suggested DistilBERT-TC-MA model on MIND dataset are better than several other advanced methods.

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Section: Preference-based News Recommendationmentioning

confidence: 99%

Section: Baselinesmentioning

confidence: 99%

A Hotspot-Aware Personalized News Recommendation Mechanism Based on DistilBERT-TC-MA

He,

Wang

2024

International Journal of Distributed Systems and Technologies

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A Survey of Personalized News Recommendation

Meng,

Huo,

Zhang

et al. 2023

Data Sci. Eng.

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Personalized news recommendation is an important technology to help users obtain news information they are interested in and alleviate information overload. In recent years, news recommendation has been increasingly widely studied and has achieved remarkable success in improving the news reading experience of users. In this paper, we provide a comprehensive overview of personalized news recommendation approaches. Firstly, we introduce personalized news recommendation systems according to different needs and analyze the characteristics. And then, a three-part research framework on personalized news recommendation is put forward. Based on the framework, the knowledge and methods involved in each part are analyzed in detail, including news datasets and processing techniques, prediction models, news ranking and display. On this basis, we focus on news recommendation methods based on different types of graph structure learning, including user–news interaction graph, knowledge graph and social relationship graph. Lastly, the challenges of the current news recommendation are analyzed and the prospect of the future research direction is presented.

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A Context-aware Interest Drift Network for Session-based News Recommendations

Cited by 2 publications

References 12 publications

A Hotspot-Aware Personalized News Recommendation Mechanism Based on DistilBERT-TC-MA

A Hotspot-Aware Personalized News Recommendation Mechanism Based on DistilBERT-TC-MA

A Survey of Personalized News Recommendation

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