research-article

Task Recommendation via Heterogeneous Multi-modal Features and Decision Fusion in Mobile Crowdsensing

Authors:

Guosheng ZhaoAuthors Info & Claims

ACM Transactions on Multimedia Computing, Communications and Applications, Volume 20, Issue 3

Article No.: 78, Pages 1 - 20

https://doi.org/10.1145/3626239

Published: 10 November 2023 Publication History

Abstract

In the decision-making process of the behavior of mobile crowdsensing, using a single view to learn a user's preference will lead to a mismatch between the user's wishes and the final task recommendation list, resulting in the low efficiency of the model recommendation. Aiming at the lack of perceptual representation and cognitive fusion of multimodal coupled information, a task recommendation method based on heterogeneous multimodal features and decision fusion is proposed. According to the content characteristics of multi-source data in the user's historical task set, several task-task similarity matrices are constructed to align feature dimensions and feature semantics. Using the improved similarity network fusion algorithm, networks composed of multiple content similarity matrices are effectively fused into a similarity network. Considering the influence of the time factor, the tasks that have had interest drift are filtered out from the set of tasks that the user has participated in. Finally, the updated similarity network is clustered to predict the current preference of the user for new tasks. Experimental results based on simulation and real datasets show that the proposed method can effectively improve the accuracy and efficiency of task assignments while improving user satisfaction.

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Gao HSu YWang FLi H(2024)Heterogeneous Fusion and Integrity Learning Network for RGB-D Salient Object DetectionACM Transactions on Multimedia Computing, Communications, and Applications10.1145/365647620:7(1-24)Online publication date: 15-May-2024
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Wang SYan YHan FTian YDing YYang PLi XOkoshi TKo JLiKamWa R(2024)MultiRider: Enabling Multi-Tag Concurrent OFDM Backscatter by Taming In-band InterferenceProceedings of the 22nd Annual International Conference on Mobile Systems, Applications and Services10.1145/3643832.3661862(292-303)Online publication date: 3-Jun-2024
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Index Terms

Task Recommendation via Heterogeneous Multi-modal Features and Decision Fusion in Mobile Crowdsensing
1. Networks
  1. Network services
    1. Network management
  2. Network types
    1. Mobile networks

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Published In

cover image ACM Transactions on Multimedia Computing, Communications, and Applications

ACM Transactions on Multimedia Computing, Communications, and Applications Volume 20, Issue 3

March 2024

665 pages

EISSN:1551-6865

DOI:10.1145/3613614

Editor:
Abdulmotaleb El Saddik
Mohamed Bin Zayed University of Artificial Intelligence, UAE and University of Ottawa, Canada

Issue’s Table of Contents

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 10 November 2023

Online AM: 02 October 2023

Accepted: 18 September 2023

Revised: 10 May 2023

Received: 23 April 2022

Published in TOMM Volume 20, Issue 3

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National Natural Science Foundation of China
Specialized Research Fund for the Doctoral Program of Higher Education of China
Natural Science Foundation of Heilongjiang Province

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Cited By

Fu LLiu YZhang YLi M(2024)Network Information Security Monitoring Under Artificial Intelligence EnvironmentInternational Journal of Information Security and Privacy10.4018/IJISP.34503818:1(1-25)Online publication date: 21-Jun-2024
https://dl.acm.org/doi/10.4018/IJISP.345038
Gao HSu YWang FLi H(2024)Heterogeneous Fusion and Integrity Learning Network for RGB-D Salient Object DetectionACM Transactions on Multimedia Computing, Communications, and Applications10.1145/365647620:7(1-24)Online publication date: 15-May-2024
https://dl.acm.org/doi/10.1145/3656476
Wang SYan YHan FTian YDing YYang PLi XOkoshi TKo JLiKamWa R(2024)MultiRider: Enabling Multi-Tag Concurrent OFDM Backscatter by Taming In-band InterferenceProceedings of the 22nd Annual International Conference on Mobile Systems, Applications and Services10.1145/3643832.3661862(292-303)Online publication date: 3-Jun-2024
https://dl.acm.org/doi/10.1145/3643832.3661862
Xue MXu ZQiao SZheng JLi TWang YPeng D(2024)Driver intention prediction based on multi-dimensional cross-modality information interactionMultimedia Systems10.1007/s00530-024-01282-330:2Online publication date: 15-Mar-2024
https://dl.acm.org/doi/10.1007/s00530-024-01282-3

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