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{
    "pk": 24380,
    "title": "Dual Contrastive Learning for Next POI Recommendation with Long and Short-Term Trajectory Modeling",
    "subtitle": null,
    "abstract": "Next point-of-interest (POI) recommendation is a challenging task that aims to recommend the next location that a user may be interested in based on their check-in trajectories. Since users travel not only with long-term stable preferences but also with short-term dynamic interests, there is often a potential dependency between long-term and short-term preferences. Most existing works tend to mine the dependencies between long-term and short-term trajectories by contrastive learning but always ignore the negative impact of the learned dependencies on the accuracy of short-term trajectory modeling. Moreover, they often only utilize the context information of the user's trajectory, while neglecting the spatiotemporal dependencies between user trajectories. To address these issues, we proposed a novel dual contrastive learning framework DCLS. Specifically, we designed a novel dual contrastive learning scheme, for which we built two views: the first view is between the user's own long-term and short-term trajectories, and the second view is between the short-term trajectories of different users. We performed contrastive learning on both views, to learn the dependency between long-term and short-term trajectories, and improve the accuracy of trajectory modeling. We also designed a multi-class attention fusion module, which integrates the spatiotemporal influence of trajectory dependencies on user mobility, enhancing the recommendation performance. We conducted extensive experiments on three real-world datasets, which demonstrated that our model achieves advanced performance in the next POI recommendation.",
    "language": "eng",
    "license": {
        "name": "",
        "short_name": "",
        "text": null,
        "url": ""
    },
    "keywords": [
        {
            "word": "Artificial Intelligence; Sociology; Behavioral Science; Decision making; Machine learning; Predictive Processing; Comparative Analysis; Computational Modeling; Computer-based experiment"
        }
    ],
    "section": "Papers with Poster Presentation",
    "is_remote": true,
    "remote_url": "https://escholarship.org/uc/item/9g25f3sx",
    "frozenauthors": [
        {
            "first_name": "Zhi",
            "middle_name": "",
            "last_name": "Liu",
            "name_suffix": "",
            "institution": "Zhejiang University of Technology",
            "department": ""
        },
        {
            "first_name": "Junhui",
            "middle_name": "",
            "last_name": "Deng",
            "name_suffix": "",
            "institution": "College of Computer Science and Technology",
            "department": ""
        },
        {
            "first_name": "Deju",
            "middle_name": "",
            "last_name": "Zhang",
            "name_suffix": "",
            "institution": "College of Computer Science and Technology, Zhejiang University of Technology",
            "department": ""
        },
        {
            "first_name": "zhiyu",
            "middle_name": "",
            "last_name": "chen",
            "name_suffix": "",
            "institution": "Computer Science and Technology",
            "department": ""
        },
        {
            "first_name": "Guojiang",
            "middle_name": "",
            "last_name": "Shen",
            "name_suffix": "",
            "institution": "Zhejiang University of Technology",
            "department": ""
        },
        {
            "first_name": "Xiangjie",
            "middle_name": "",
            "last_name": "Kong",
            "name_suffix": "",
            "institution": "Zhejiang University of Technology",
            "department": ""
        }
    ],
    "date_submitted": null,
    "date_accepted": null,
    "date_published": "2024-01-02T00:00:00+06:00",
    "render_galley": null,
    "galleys": [
        {
            "label": "PDF",
            "type": "pdf",
            "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24380/galley/13977/download/"
        },
        {
            "label": "PDF",
            "type": "pdf",
            "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24380/galley/21109/download/"
        }
    ]
}