Intelligent human-device interfaces play key roles in fully automated vehicles (FAVs), ensuring smooth interactions and improving the driving experience. Listening to news is a popular method of relaxing during a journey; as a result, travelers require automatic recommendations of preferred news programs. Most existing news recommender systems usually learn topic-level representations of users and news for recommendations while neglecting to learn more informative aspect-level features, resulting in limited recommendation performance. To bridge this significant gap, we propose a novel Aspect-driven News Recommender System (ANRS) built on aspect-level user preferences and news representation learning. In ANRS, a news aspect-level encoder and a user aspect-level encoder are devised to learn the fine-grained aspect-level representations of users’ preferences and news characteristics respectively. These representations are subsequently fed into a click predictor to predict the probability of a given user clicking on the candidate news item. Extensive experiments demonstrate the superiority of our method over state-of-the-art baseline methods.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Aspect-Driven User Preference and News Representation Learning for News Recommendation


    Beteiligte:
    Lu, Wenpeng (Autor:in) / Wang, Rongyao (Autor:in) / Wang, Shoujin (Autor:in) / Peng, Xueping (Autor:in) / Wu, Hao (Autor:in) / Zhang, Qian (Autor:in)

    Erschienen in:

    Erscheinungsdatum :

    01.12.2022


    Format / Umfang :

    1678193 byte




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Reinforcement recommendation with user multi-aspect preference

    Chen, X / Du, Y / Xia, L et al. | BASE | 2021

    Freier Zugriff

    REPORT,NEWS,REPRESENTATION

    KIM KYONG BOK | Europäisches Patentamt | 2016

    Freier Zugriff


    Parking recommendation system based on user preference and parking space occupancy rate

    YAN PENGYU / XIE HAOYU / CAI XIAOQIANG | Europäisches Patentamt | 2023

    Freier Zugriff

    Drums-IBC User News

    Online Contents | 1993