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Collaborative, dynamic and diversified user profiling

Published: 27 January 2019 Publication History

Abstract

In this paper, we study the problem of dynamic user profiling in the context of streams of short texts. Previous work on user profiling works with long documents, do not consider collaborative information, and do not diversify the keywords for profiling users' interests. In contrast, we address the problem by proposing a user profiling algorithm (UPA), which consists of two models: the proposed collaborative interest tracking topic model (CITM) and the proposed streaming keyword diversification model (SKDM). UPA first utilizes CITM to collaboratively track each user's and his followees' dynamic interest distributions in the context of streams of short texts, and then utilizes SKDM to obtain top-k relevant and diversified keywords to profile users' interests at a specific point in time. Experiments were conducted on a Twitter dataset and we found that UPA outperforms state-of-the-art non-dynamic and dynamic user profiling algorithms.

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        cover image Guide Proceedings
        AAAI'19/IAAI'19/EAAI'19: Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence and Thirty-First Innovative Applications of Artificial Intelligence Conference and Ninth AAAI Symposium on Educational Advances in Artificial Intelligence
        January 2019
        10088 pages
        ISBN:978-1-57735-809-1

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        • Association for the Advancement of Artificial Intelligence

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        AAAI Press

        Publication History

        Published: 27 January 2019

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        • (2024)Knowledge Graph Embedding: A Survey from the Perspective of Representation SpacesACM Computing Surveys10.1145/3643806Online publication date: 2-Feb-2024
        • (2024)Developing personas for live streaming commerce platforms with user survey dataUniversal Access in the Information Society10.1007/s10209-023-00996-x23:4(1705-1721)Online publication date: 1-Nov-2024
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        • (2021)Learning Dynamic User Behavior Based on Error-driven Event RepresentationProceedings of the Web Conference 202110.1145/3442381.3450012(2457-2465)Online publication date: 19-Apr-2021

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