research-article

A Novel Approach using Context Matching Algorithm and Knowledge Inference for User Identification in Social Networks

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Hai Van Pham,

Van Thai NguyenAuthors Info & Claims

ICMLSC '20: Proceedings of the 4th International Conference on Machine Learning and Soft Computing

Pages 149 - 153

https://doi.org/10.1145/3380688.3380708

Published: 07 March 2020 Publication History

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Abstract

User identifications are in searching Online Social Networks (OSN) to find identical users among different social sites in many data sources (data integration, data enrichment, information retrieval,...). However, these user-unique attributes are difficult to obtain due to privacy issues. It is hard to identify users across multiple OSNs online. This paper has presented user's identification across multiple OSNs in order to develop searching engine for user identification. The proposed approach is designed to find by searching engine while accommodating User identifications in searching Online Social Networks (OSN). Experimental results demonstrate that our proposed approach achieves a significant improvement in term of performance accuracy.

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Cited By

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Pham VNguyen QTruong VTran L(2022)The Proposed Context Matching Algorithm and Its Application for User Preferences of Tourism in COVID-19 PandemicInternational Conference on Innovative Computing and Communications10.1007/978-981-19-2535-1_22(285-293)Online publication date: 23-Sep-2022
https://doi.org/10.1007/978-981-19-2535-1_22
Van Pham HTien D(2021)Hybrid Louvain-Clustering Model Using Knowledge Graph for Improvement of Clustering User’s Behavior on Social NetworksIntelligent Systems and Networks10.1007/978-981-16-2094-2_16(126-133)Online publication date: 13-May-2021
https://doi.org/10.1007/978-981-16-2094-2_16
Tien DVan H(2020)Graph Neural Network Combined Knowledge Graph for Recommendation SystemComputational Data and Social Networks10.1007/978-3-030-66046-8_6(59-70)Online publication date: 11-Dec-2020
https://dl.acm.org/doi/10.1007/978-3-030-66046-8_6

Index Terms

A Novel Approach using Context Matching Algorithm and Knowledge Inference for User Identification in Social Networks
1. Computing methodologies
  1. Artificial intelligence
    1. Knowledge representation and reasoning

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Published In

ICMLSC '20: Proceedings of the 4th International Conference on Machine Learning and Soft Computing

January 2020

175 pages

ISBN:9781450376310

DOI:10.1145/3380688

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 ACM 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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NICT: National Institute of Information and Communications Technology

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 07 March 2020

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ICMLSC 2020

ICMLSC 2020: The 4th International Conference on Machine Learning and Soft Computing

January 17 - 19, 2020

Haiphong City, Viet Nam

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Pham VNguyen QTruong VTran L(2022)The Proposed Context Matching Algorithm and Its Application for User Preferences of Tourism in COVID-19 PandemicInternational Conference on Innovative Computing and Communications10.1007/978-981-19-2535-1_22(285-293)Online publication date: 23-Sep-2022
https://doi.org/10.1007/978-981-19-2535-1_22
Van Pham HTien D(2021)Hybrid Louvain-Clustering Model Using Knowledge Graph for Improvement of Clustering User’s Behavior on Social NetworksIntelligent Systems and Networks10.1007/978-981-16-2094-2_16(126-133)Online publication date: 13-May-2021
https://doi.org/10.1007/978-981-16-2094-2_16
Tien DVan H(2020)Graph Neural Network Combined Knowledge Graph for Recommendation SystemComputational Data and Social Networks10.1007/978-3-030-66046-8_6(59-70)Online publication date: 11-Dec-2020
https://dl.acm.org/doi/10.1007/978-3-030-66046-8_6

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Characterizing user behavior in online social networks

Characterizing user navigation and interactions in online social networks

Social exchange in online social networks. The reciprocity phenomenon on Facebook