skip to main content
10.1145/2532443.2532459acmotherconferencesArticle/Chapter ViewAbstractPublication PagesinternetwareConference Proceedingsconference-collections
research-article

Enhancing trustworthiness evaluation in internetware with similarity and non-negative constraints

Published: 23 October 2013 Publication History

Abstract

Internetware is envisioned as a new software paradigm where software developers usually need to interact with unknown partners as well as the software entities developed by them. To reduce uncertainty and boost collaborations in such setting, it is important to provide trustworthiness evaluation mechanisms so that trustworthy partners/entities can be easily found. In this work, we propose a novel trustworthiness evaluation mechanism by enhancing existing mechanisms with similarity and non-negative constraints. To be specific, we first extend an existing multi-aspect trust inference model by incorporating the non-negative constraint. One of the advantages of such constraint is its strong interpretability. Second, we incorporate similarity into two neighborhood models borrowed from recommender systems. When computing similarity, we make use of the intermediate results from the first step. Finally, these models are combined under a machine learning framework. To show the effectiveness of our method, we conduct experiments on a real data-set. The results show that: both our non-negativity extension and similarity computation improve the evaluation accuracy of the original methods, and the combined method outperforms several state-of-the-art methods.

References

[1]
J. Lu, X. Ma, X. Tao, F. Xu, and H. Hu. Research and progress on Internetware. Science in China (Series E), 36(10): 1037--1080, 2006.
[2]
J. Lu, X. Tao, X. Ma, H. Hu, F. Xu, and C. Cao. Research on agent-based Internetware. Science in China (Series E), 35(12): 1--21, 2005.
[3]
Y. Yao, F. Xu, Y. Ren, H. Tong, and J. Lu. SelfTrust: Leveraging Self-Assessment for Trust Inference in Internetware. Accepted by Science in China (Series E).
[4]
L. Li, Y. Wang, and E. P. Lim. Trust-oriented composite service selection and discovery. In Proc. of the 7th International Joint Conference on Service-Oriented Computing, pages 50--67. Springer-Verlag, 2009.
[5]
C. W. Hang and M. P. Singh. Trustworthy service selection and composition. ACM Transactions on Autonomous and Adaptive Systems (TAAS), 6(1): 5, 2011.
[6]
Audun Jøsang, Roslan Ismail, and Colin Boyd. A survey of trust and reputation systems for online service provision. Decision Support Systems, 43(2): 618--644, 2007.
[7]
Yuan Yao, Hanghang Tong, Feng Xu, and Jian Lu. Subgraph Extraction for Trust Inference in Social Networks. ASONAM, page 163--170, 2012.
[8]
Yuan Yao, Hanghang Tong, Xifeng Yan, Feng Xu, and Jian Lu. MATRI: A Multi-Aspect and Transitive Trust Inference Model. WWW, page 1467--1476, 2013.
[9]
J. Golbeck. Trust and nuanced profile similarity in online social networks. ACM Transactions on the Web, vol. 3, no. 4, page 12, 2009.
[10]
R. Xiang, J. Neville, and M. Rogati. Modeling relationship strength in online social networks. WWW. page 981--990, 2010.
[11]
Andriy Mnih, and Ruslan Salakhutdinov. Probabilistic matrix factorization. NIPS, page 1257--1264, 2007.
[12]
D. Seung, and l. Lee. Algorithms for non-negative matrix factorization. NIPS, page 556--562, 2001.
[13]
Y. Koren. Factorization meets the neighborhood: a multifaceted collaborative filtering model. KDD. pp. 426--434, 2008.
[14]
Li Xiong and Ling Liu. Peertrust: Supporting reputation-based trust for peer-to-peer electronic communities. IEEE Transactions on Knowledge and Data Engineering, 16(7): 843--857, 2004.
[15]
Runfang Zhou and Kai Hwang. Powertrust: A robust and scalable reputation system for trusted peer-to-peer computing. IEEE Transactions on Parallel and Distributed Systems, 18(4): 460--473, 2007.
[16]
C. Ziegler and J. Golbeck. Investigating interactions of trust and interest similarity. Decision Support Systems, vol. 43, no. 2, pp. 460--475, 2007.
[17]
Alfarez Abdul-Rahman and Stephen Hailes. Supporting trust in virtual communities. Annual Hawaii International Conference on System Sciences, 2000.
[18]
Seung, D., and Lee, L. Algorithms for non-negative matrix factorization. Advances in neural information processing systems, 13, 556--562, 2001.
[19]
Hoyer, P. O. Non-negative matrix factorization with sparseness constraints. The Journal of Machine Learning Research, 5, 1457--1469, 2004.
[20]
C. Hsieh, K. Chiang, and I. Dhillon. Low rank modeling of signed networks. In KDD, pages 507--515. ACM, 2012.
[21]
C.-W. Hang, Y. Wang, and M. P. Singh. Operators for propagating trust and their evaluation in social networks. In AAMAS, pages 1025--1032, 2009.

Cited By

View all
  • (2018)A Unified Measurement Solution of Software Trustworthiness Based on Social-to-Software FrameworkJournal of Computer Science and Technology10.1007/s11390-018-1843-233:3(603-620)Online publication date: 11-May-2018

Index Terms

  1. Enhancing trustworthiness evaluation in internetware with similarity and non-negative constraints

        Recommendations

        Comments

        Information & Contributors

        Information

        Published In

        cover image ACM Other conferences
        Internetware '13: Proceedings of the 5th Asia-Pacific Symposium on Internetware
        October 2013
        211 pages
        ISBN:9781450323697
        DOI:10.1145/2532443
        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]

        Sponsors

        • NJU: Nanjing University
        • CCF: China Computer Federation
        • Chinese Academy of Sciences

        Publisher

        Association for Computing Machinery

        New York, NY, United States

        Publication History

        Published: 23 October 2013

        Permissions

        Request permissions for this article.

        Check for updates

        Author Tags

        1. internetware
        2. multi-aspect
        3. non-negativity
        4. similarity
        5. trustworthiness evaluation

        Qualifiers

        • Research-article

        Funding Sources

        Conference

        Internetware '13
        Sponsor:
        • NJU
        • CCF

        Acceptance Rates

        Internetware '13 Paper Acceptance Rate 15 of 50 submissions, 30%;
        Overall Acceptance Rate 55 of 111 submissions, 50%

        Contributors

        Other Metrics

        Bibliometrics & Citations

        Bibliometrics

        Article Metrics

        • Downloads (Last 12 months)2
        • Downloads (Last 6 weeks)0
        Reflects downloads up to 20 Jan 2025

        Other Metrics

        Citations

        Cited By

        View all
        • (2018)A Unified Measurement Solution of Software Trustworthiness Based on Social-to-Software FrameworkJournal of Computer Science and Technology10.1007/s11390-018-1843-233:3(603-620)Online publication date: 11-May-2018

        View Options

        Login options

        View options

        PDF

        View or Download as a PDF file.

        PDF

        eReader

        View online with eReader.

        eReader

        Media

        Figures

        Other

        Tables

        Share

        Share

        Share this Publication link

        Share on social media