Modelling Behavior for the Optimization of Mobile Interactions and Supply--Demand Alignment for Sharing Economy Platforms.
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| Title: | Modelling Behavior for the Optimization of Mobile Interactions and Supply--Demand Alignment for Sharing Economy Platforms. |
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| Authors: | Ma, Zhaohe1 hedy_mazhaohe@163.com |
| Source: | International Journal of Interactive Mobile Technologies. 2026, Vol. 20 Issue 14, p117-131. 15p. |
| Subjects: | Human behavior models, Supply & demand, Mobile operating systems, Edge computing, Ridesharing services, Selectivity (Psychology) |
| Abstract: | Shared mobility platforms rely on mobile terminals to support large-scale service scheduling. However, the limited computational resources of mobile devices and the reliance of existing approaches on trajectory data alone have resulted in insufficient demand perception accuracy and elevated supply--demand matching latency, primarily because dynamic user interaction behaviors have been overlooked. To address these limitations, a progressive and integrated framework encompassing mobile sensing, behavior modeling, and edge-assisted matching was developed to enable fine-grained user behavior modeling and realtime supply--demand optimization in shared mobility environments. Mobile interaction entropy and conditional interaction entropy were introduced to quantify the degree of operational disorder and the temporal regularity of user behaviors, respectively. A lightweight dual-stream attention network was designed to fuse trajectory-based spatial features with interaction-behavior features, thereby facilitating accurate short-term travel demand prediction. A weighted loss function was incorporated to strengthen the fitting performance of difficult-to-predict scenarios. Within an edge computing architecture, dynamic contextual matching criteria were established through online metric learning with positive-definite constraints, while locality-sensitive hashing was employed to accelerate candidate retrieval and achieve millisecond-level supply--demand matching. Furthermore, a closed-loop edge--cloud collaborative updating mechanism was developed to balance local environmental adaptability with global model generalization. [ABSTRACT FROM AUTHOR] |
| Copyright of International Journal of Interactive Mobile Technologies is the property of International Journal of Interactive Mobile Technologies and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
| FullText | Links: – Type: pdflink Text: Availability: 0 |
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| Header | DbId: egs DbLabel: Engineering Source An: 195570692 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Modelling Behavior for the Optimization of Mobile Interactions and Supply--Demand Alignment for Sharing Economy Platforms. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Ma%2C+Zhaohe%22">Ma, Zhaohe</searchLink><relatesTo>1</relatesTo><i> hedy_mazhaohe@163.com</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22International+Journal+of+Interactive+Mobile+Technologies%22">International Journal of Interactive Mobile Technologies</searchLink>. 2026, Vol. 20 Issue 14, p117-131. 15p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Human+behavior+models%22">Human behavior models</searchLink><br /><searchLink fieldCode="DE" term="%22Supply+%26+demand%22">Supply & demand</searchLink><br /><searchLink fieldCode="DE" term="%22Mobile+operating+systems%22">Mobile operating systems</searchLink><br /><searchLink fieldCode="DE" term="%22Edge+computing%22">Edge computing</searchLink><br /><searchLink fieldCode="DE" term="%22Ridesharing+services%22">Ridesharing services</searchLink><br /><searchLink fieldCode="DE" term="%22Selectivity+%28Psychology%29%22">Selectivity (Psychology)</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Shared mobility platforms rely on mobile terminals to support large-scale service scheduling. However, the limited computational resources of mobile devices and the reliance of existing approaches on trajectory data alone have resulted in insufficient demand perception accuracy and elevated supply--demand matching latency, primarily because dynamic user interaction behaviors have been overlooked. To address these limitations, a progressive and integrated framework encompassing mobile sensing, behavior modeling, and edge-assisted matching was developed to enable fine-grained user behavior modeling and realtime supply--demand optimization in shared mobility environments. Mobile interaction entropy and conditional interaction entropy were introduced to quantify the degree of operational disorder and the temporal regularity of user behaviors, respectively. A lightweight dual-stream attention network was designed to fuse trajectory-based spatial features with interaction-behavior features, thereby facilitating accurate short-term travel demand prediction. A weighted loss function was incorporated to strengthen the fitting performance of difficult-to-predict scenarios. Within an edge computing architecture, dynamic contextual matching criteria were established through online metric learning with positive-definite constraints, while locality-sensitive hashing was employed to accelerate candidate retrieval and achieve millisecond-level supply--demand matching. Furthermore, a closed-loop edge--cloud collaborative updating mechanism was developed to balance local environmental adaptability with global model generalization. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of International Journal of Interactive Mobile Technologies is the property of International Journal of Interactive Mobile Technologies and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.3991/ijim.v20i14.62555 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 15 StartPage: 117 Subjects: – SubjectFull: Human behavior models Type: general – SubjectFull: Supply & demand Type: general – SubjectFull: Mobile operating systems Type: general – SubjectFull: Edge computing Type: general – SubjectFull: Ridesharing services Type: general – SubjectFull: Selectivity (Psychology) Type: general Titles: – TitleFull: Modelling Behavior for the Optimization of Mobile Interactions and Supply--Demand Alignment for Sharing Economy Platforms. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Ma, Zhaohe IsPartOfRelationships: – BibEntity: Dates: – D: 15 M: 07 Text: 2026 Type: published Y: 2026 Identifiers: – Type: issn-print Value: 18657923 Numbering: – Type: volume Value: 20 – Type: issue Value: 14 Titles: – TitleFull: International Journal of Interactive Mobile Technologies Type: main |
| ResultId | 1 |
