Zeinab Noorian


Short Bio

I am a NSERC Postdoctoral Fellow at the LS3 lab of the Ryerson university. I am also a Visitor Researcher in IBM Centres for Advance Studies (CAS) since May 2016. 
I hold
 a Ph.D degree (Aug 2013) in Computer Science from the University of New Brunswick where I earned the best Graduate Thesis Award.
Previously, I was a Postdoctoral Researcher at Data Science Lab of Ryerson University from Aug 2015-Dec 2015, and a Postdoctoral Research Fellow at MADMUC Laboratory of University of Saskatchewan from Aug 2013- Sep 2014. 
I am also an adjunct professor of Mazandaran University of Science and Technology since Feb 2015.
Alongside my professional life, my hobbies include playing Santoor,  working out, cooking and hanging out with my friends and family.


My research interest are:

  • Social Media Analytics
  • Recommender Systems
  • Social Networks
  • Machine Learning and Data Mining
  • Trust and Reputation Systems
  • Adaptive User Modelling Personalization, Adaptation and Recommendation
  • E-commerce Systems


  • Call For Paper:  Special Issue on Mining Actionable Insights from Social Network with journal of information system.
  • Call For Paper:  WSDN 2017 Workshop on Mining Actionable insights from Social Network (MAISoN'17).
  • Call For Paper:  AAAI 2016 Workshop on Incentives and Trust in E-Communities (WIT-EC'16).
  • Call For Paper:  AAAI 2015 Workshop on Incentives and Trust in E-Communities (WIT-EC'15).
  • Call For Paper:  AAAI 2014 Workshop on Incentives and Trust in E-Communities (WIT-EC'14).
  • Call For Paper: The 8th IFIP Conference on Trust Management (IFIPTM 2014), Singapore, July 2014. 
  • Call For Paper: Special issue of Computational Intelligence journal on Incentives and Trust in E-Commerce.
  • Proceedings of the IJCAI 2013 Workshop on Incentive and Trust (WIT-EC'13) is here to download!
  • Proceedings of EC ACM 2012 workshop on Incentive and Trust (WIT-EC'12) is here to download!

Recent Activity

  • Co-Chair of WSDN Workshop of Mining Actionable Insight from Social Network: (MAISoN'17).
  • Co-Editor of Special Issue on Mining Actionable Insights from Social Network with journal of information system.
  • Co-Chair of annual AAAI Workshop on Incentive and Trust in E-Communities: WIT-EC'14, WIT-EC'15, and WIT-EC'16.
  • Co-Chair of 2014 IFIP Trust Management, Singapore. 
  • Co-Chair of  IJCAI 2013 workshop on Incentive and Trust in E-Commerce (WIT-EC'13). Beijing, China, August 2013.
  • Guest Editor of the special issue of Computational Intelligence Journal on Incentive and Trust in E-commerce.
  • 16 July 2012:   Invited talk for the TRUM'12 Workshop at Montreal, Canada.
  • 08 June 2012 : Attended the WIT-EC 2012workshop in Valencia as an paper author and organizer
  • 30 May 2012 : Paper presentation on Canadian AI 2012. 
  •  Co-Chair of ACM EC 2012 Worshop on Incentive and Trust in e-commerce (WIT-EC 2012). Valencia, Spain, June 2012. 
  • 30 June 2011 :  Paper presentation at IFIPTM 2011 in Copenhagen, Denmark. 
  • 20-24 June 2011 : Attended on the IFIPTM 2011 Summer School in Copenhagen,Denmark, 2011
  • 31 May 2010: Paper presentation at Canadian AI 2010 Graduate Symposium.



  • Zeinab Noorian, Stephen Marsh, Michael Fleming: zTrust: Adaptive Decentralized Trust Model for Quality of Service Selection in Electronic Marketplaces. Computational Intelligence 32(1): 127-164, 2016.
  • Mehrnaz Ghashghaei; Ebrahim Bagheri; John Cuzzola; Ali A. Ghorbani, Zeinab Noorian, SemanticDisambiguation and Linking of Quantitative Mentions in Textual Content. International Journal of Semantic Computing 10(1):121-142, 2016.
  • Wu, K., Vassileva, J., Zhao, Y., Zeinab Noorian, Waldner, W., Adaji, I. Complexity or simplicity? Designing product pictures for advertising in online marketplaces. Journal of Retailing and Consumer Services, 28, 17-27, 2016
  • Wu, K., Vassileva, J., Zeinab Noorian, Zhao, Y. How do you feel when you see a list of prices? The interplay among price dispersion, perceived risk and initial trust in Chinese C2C market. Journal of Retailing and Consumer Services, 25, 36-46, 2015.
  • Wu, K., Zeinab Noorian, Vassileva, J., Adaji, I. How buyers perceive the credibility of advisors in online marketplace: review balance, review count and misattribution. Journal of Trust Management, 2(1), 1-18, 2015.
  • Zeinab Noorian, Jie Zhang, Yuan Liu, Stephen Marsh and Michael Fleming: Trust-Oriented Buyer Strategies for Seller Reporting and Selection in Competitive Electronic Marketplaces. Autonomous Agents and Multi-Agent Systems 28(6): 896-933, 2014.
  • Zeinab Noorian, Mihaela Ulieru: The State of the Art in Trust and Reputation Systems: A Framework for Comparison. Journal of Theoretical and Applied Electronic Commerce Research 5(2): 97-117, 2010.


  • Mohsen Mohkami, Zeinab Noorian, Julita Vassileva. Dynamic Credibility Threshold Assignment in Trust and Reputation Mechanisms Using PID Controller. International Conference on Collaboration and Technology (CRIWG'15). Yerevan, Armenia, 2015.
  • Zeinab Noorian, Mohsen Mohkami, Julita Vassileva: How much trust is enough to trust? A market adaptive trust threshold setting for e-marketplaces, European Conference in Articial Intelligence, ECAI'14: 663-668, 2014.
  • Zeinab Noorian, Mohsen Mohkami, Julita Vassileva: Self-Adaptive Filtering Using PID Feedback Controller in Electronic Commerce, ACM-HyperText (HT'14): 267-272, 2014.
  • Zeinab Noorian, Mohsen Mohkami, Yuan Liu, Hui Fang, Julita Vassileva, Jie Zhang: SocialTrust: Adaptive Trust Oriented Incentive Mechanism for Social Commerce, International Conference on Web Intelligence (WIC'14), 2014.
  • Zeinab Noorian, Johnson Iyilade, Mohsen Mohkami, Julita Vassileva: Trust Mechanism for Enforcing Compliance to Secondary Data Use Contracts, Privacy, Security and Trust Conference. 2014.
  • Kewen Wu, Zeinab Noorian , Julita Vassileva. What if the Advisors are not Trustworthy? Evaluating the Trustworthiness of Advisors in a "Lemon" C2C Market. AAAI Workshop on Incentive and Trust in Electronic Communities (WIT-EC '14), 2014.
  • Zeinab Noorian, Jie Zhang, Yuan Liu, Michael Fleming and Stephen Marsh: Determining the Optimal Reporting Strategy in Competitive E-Marketplaces. The 11th IEEE International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom'12): 350-357, 2012.
  • Zeinab Noorian, Mahdi Noorian, Michael Fleming, Stephen Marsh: A Strategic Reputation-Based Mechanism for Mobile Ad Hoc Networks. Canadian Conference on AI 2012: 145-157, 2012.
  • Zeinab Noorian, Michael Fleming and Stephen Marsh. Preference-Oriented QoS-based Service Discovery with Dynamic Trust and Reputation Management. ACM Symposium on Applied Computing (ACM-SAC'12): 2014-2021, 2012.
  • Zeinab Noorian, Modeling Buyers in Competitive Electronic Marketplace Environments. In the workshop proceeding of the 20th conference on User Modeling, Adaptation, and Personalization (UMAP), 2012.
  • Zeinab Noorian, Michael Fleming and Stephen Marsh, Towards a design of Adaptive Incentive Mechanism for Large e-Marketplace. In the proceeding of Workshop on Incentive and Trust in e-commerce: 48-63, 2012.
  • Zeinab Noorian, Stephen Marsh, and Michael Fleming. Prob-Cog: an Adaptive Filtering Model for Trust Evaluation. In the proceeding of International Conference on Trust Management (IFIPTM 2011): 206-222, 2011.
  • Ehsan Mokhtari, Zeinab Noorian and Behrouz Tork Ladani, A Context-aware Reputation-based Model of Trust for Open Multi-Agent Environments.Canadian Conference on AI: 301-312, 2011.
  • Zeinab Noorian, Stephen Marsh, and Michael Fleming. Multi-layer cognitive filtering by behavioural modeling. In a 10th international conference on Autonomous agents and Multiagent systems (AAMAS 2011):871-878, ACM, 2011.
  • Zeinab Noorian, Multi-Layered Cognitive Filtering by Behavioural Modeling. poster presentation on International Conference on Trust Management, 2011.
  • Zeinab Noorian, An Adaptive Trust and Reputation System for Open Dynamic Environment. Canadian Conference on AI 2010: 422-423. 2010.
  • Zeinab Noorian, A Trust and Reputation Framework for Open Dynamic Systems, Proceeding of the Seventh Annual UNB Research Exposition, 2010.
  • Zeinab Noorian, Hadi Hosseini and Mihaela Ulieru An Autonomous Agent-based Framework for Self Healing Power Grid, IEEE International Conference on Systems, Man and Cybernetics (IEEE-SMC): 1983-988, 2009.
  • Mahdi Noorian, Hamidreza Pooshfam, Zeinab Noorian, Rosni Abdullah. Performance enhancement of Smith-Waterman algorithm using hybrid model: Comparing the MPI and hybrid programming paradigm on SMP clusters, IEEE International Conference on Systems, Man and Cybernetics (IEEE-SMC): 492-497, 2009.
  • Mahdi Noorian, Zeinab Noorian, Parallel Smith-Waterman Algorithm on Cluster of SMP Machine, Proceeding of the Sixth Annual UNB Research Exposition, 2009.
  • Zeinab Noorian, An Agent-based Self-Healing Framework for Power Grid, Proceeding of the Sixth Annual UNB Research Exposition, 2009.



zTrust: Adaptive Decentralized Trust Model for Quality of Service Selection in Electronic Marketplaces

My PhD research focused on detecting fraudulent users with misleading purchase behaviour in electronic marketplace. I proposed a computational model of trust which combines the cognitive and probabilistic view of trust and consider different environmental circumstances to evaluate trustworthiness of participants in e-commerce systems.  In the extensive review of the literature (published in journal of JTAER) I introduced a multidimensional framework, which articulates essential elements in establishing trust in online communities such as e-commerce, p2p networks, ad hoc networks and cloud computing. In my PhD I also explore the human factors reported in the psychological literature and economic science and propose a cognitive and subjective model for trust evaluation and decision making as a controlling mechanism for different types of environments including cooperative and competitive electronic commerce. Empirical results (published in AAMAS; journal of AAMAS;  journal Computational Intelligence showed the effectiveness of quantifying human dispositions and their cognitive features including their competency, honesty and willingness in modelling trust for a cooperative and competitive e-commerce.
For more information, please read my thesis.

Dynamic Credibility Threshold Assignment in Trust and Reputation Mechanisms

One research challenge that has bugged me being widely neglected in the literature of trust models was their naive approach in setting the minimum level of trustworthiness of participants, in other words, the trust value threshold. This is very important, since inappropriately set thresholds would filter away possibly good advice, or the opposite - allow malicious users to badmouth good services. There has been no systematic approach for setting the honesty threshold.  I proposed a self-adaptive honesty threshold management mechanism based on PID feedback controller.  Experimental results show that adaptively tuning the honesty threshold to the market performance enables honest users to obtain higher quality of services in comparison with static threshold values defined by intuition and used in previous work.  
For more information, please refer to How much trust is enough to trust? A market-adaptive trust threshold setting for e-marketplaces.

Adaptive Trust Oriented Incentive Mechanism for Social Commerce

Between you and me, people are usually act selfishly, specifically when there is no reward or punishment  involved. This is more evident in virtual environment when people are able to act anonymously so there is no incentive for them to act truthfully. In other words, in the absence of legal authorities and enforcement mechanisms in open e-marketplaces, it is extremely challenging for a user to validate the quality of opinions (i.e. ratings and reviews) of products or services provided by other users. Rationally, advisers tend to be reluctant to share their truthful experience with others. I propose an adaptive incentive mechanism, where advisers are motivated to share their actual experiences with their trustworthy peers (friends/neighbors in the social network) in e-marketplaces (social commerce context), and malicious users will be eventually evacuated from the systems. Experimental results demonstrate the effectiveness of our mechanism in promoting the honesty of users in sharing their past experiences.
For more information, please read SocialTrust: Adaptive Trust Oriented Incentive Mechanism for Social Commerce.

Trust Mechanism for Enforcing Compliance to Secondary Data Use Contracts

One of the controversial issue is how much we should allow giant companies to access and use our data. There is no doubt that companies like Google Inc.  use our search histories to improve their personalized recommendation and we are thankful for that, but the question is to what degree do we have a control over our shared data? In other words, should we allow them to give our data to other companies without our permission?, and what are the available preventive measure countermeasures?  As has been mentioned, concerns regarding privacy arise when sharing user data with unknown third parties. These concerns can be alleviated at two stages: i) ensuring selective control of the applications to share user data with, and ii) monitoring and penalizing errant data consumers who violate the terms of their contractual agreement and potentially abuse user data. We propose a trust management mechanism for monitoring data consumers’ compliance to the contractual agreements for which data was shared with them. The trust mechanism is based on user complaints about suspected privacy violations and is able to identify the data consumers who are responsible. The framework penalizes the data consumer found guilty of violating its data use agreement by decreasing its trust value. This makes the data consumer less likely to be selected to receive user data, and limits its participation in the user data marketplace, forcing it to pay a higher price for purchase of user data.
For those who are interested to learn more, please refer to Trust Mechanism for Enforcing Compliance to Secondary Data Use Contracts,

News Positioning Framework for Globe and Mail

Working on the funding supported by Ontario Centre of Excellence, I have taken a lead on  a research project on news ranking framework for Globe and Mail news agency. While being one of the largest news agency in Canada, Globe and Mail uses the opinion of the expert editors to rank news on homepage which sounds not very efficient and cost-effective.
To attract more visitor to their website, they require to display  personalized news for each visitor given their clicking/browsing behaviour as well as their demographic information. At the first stage of the project, we proposed a news ranking model which predict location of the news on the homepage in terms of  freshness, the reputation of news source and authors, news generation flow; and keyword importance. In the later step, we intend to incorporate the user models into our framework to provide personalized recommendation to users.


Working with several master and phd students opened a new direction of research for me and I get involved in numerous amazing research lines. The most important ones are summarized as follows:

One of the research that I collaborated  is related to mining information from social media for the cold-item problem. While popular products receive many reviews, many other products do not have an adequate number of reviews leading to the cold item problem. We propose a solution outline for the cold item problem by automatically generating reviews and predicting ratings for the cold products from available reviews of similar products in e-commerce websites as well as users' opinion shared in the microblogging platforms such as Twitter. We propose a framework to build a formal semantic representation of products from unstructured product descriptions, user reviews as well as user ratings. Such presentations assist us to measure product similarity and relatedness in a accurate and cost-effective way.

Another research that I served as an advisor is related to detecting life events from twitter based on temporal semantic features. In this research we intend to detect important life events from user-generated social content. Life events, such as marriage, travel, and career change, among others, are difficult to detect because : i) they are specific to a given user and do not have a wider reaching reflection; ii) they are often not reported directly and need to be inferred from the content posted by individual users; and iii) many users do not report their life events on social platforms, making the problem highly class-imbalanced.In this research, we propose a semantic approach based on word embedding literature to model instances of life events.

As part of being IBM visiting scholar, we have engaged in a collaborative research with IBM fellows since Jan 2016; and has  developed an advance searching mechanism to find vulnerabilities and security issue from security management systems such as IBM AppScan Enterprise. Our final product showed a significant improvement in security issue retrieval compared with IBM existing search system. We also wrote two patents on the topics of ambiguity resolution for security data, and recommending the most relevant and urgent security issue to the security analyst.

I have supervised couples of Msc students since Dec 2015, working on the field of recommender system. Focusing on the user-generated data in a social media, they proposed personalized news recommender system by extracting implicit and explicit user's interest using word embedding methods and build a user model adaptively. Another research is related to Ad recommender system which enable different businesses to show a personalized ad to social media users based on their interest, demographic information and social structure.
The last but not least is the work that is done in activity recommender system. While users might feel confused about possible activities they can potentially engage in their leisure time, our proposed time-aware recommender system would recommend a range of activities that might be of interest of users by dynamically modeling users in different time slots.


Selected Awards and Grants

  • NSERC PostDoctoral Fellowship, 2015-2017. 
  • Best Graduate Thesis Award, University of New Brunswick, Canada, 2013.  
  • Graduate Student Scholarship, Faculty of Computer Science, University of New Brunswick, 2008-2013.
  • International Graduate Differential Fee Scholarship, University of New Brunswick, 2008-2013.
  • AAMAS Student Scholarship , the 10th international conference on Autonomous agents and Multiagent systems (AAMAS’11), 2011.
  • Graduate Symposium Grant, Canadian Conference of Artificial Intelligence, 2010.
  • Best Research Poster award in Research Exposition 2009, University of New Brunswick, 2009.
  • Certificate of achievement in the peer mentor program of the faculty of computer science at University of New Brunswick, 2011.

Conference and Workshop Organization

  • PC of the 23rd Canadian Conference on Artificial Intelligence.
  • Reviewer of the Web Intelligence Conference (WIC 2010).


  • Special issue on Mining Actionable Insights from Social Networks. Information Systems Journal- (Co editor with Ebrahim Bagheri, Faezeh Ensan, Ioannis Katakis), 2017.
  • Jie Zhang, Zeinab Noorian, Stephen Marsh: Incentives and Trust in Electronic Communities, AAAI Workshops WS-16-09, AAAI Press, ISBN 978-1-57735-759-9, 2016.
  • Zeinab Noorian, Jie Zhang, Stephen Marsh, Christian Damsgaard Jensen: Incentive and Trust in E-Communities. AAAI Workshops WS-15-08, AAAI Press, ISBN 978-1-57735-719-3, 2015.
  • Special issue on Incentive and Trust in e-communities. Trust Management 2014) Journal (co-edited with Jie Zhang and Stephen Marsh), 2014.
  • Special issue on Incentive and Trust in e-communities, Computational Intelligence Journal (co-edited with Jie Zhang and Stephen Marsh), 2012.

Journal peer-review activity

  • Journal of Autonomous Agents and MultiAgent Systems (JAAMAS).
  • IEEE Transaction on Service Computing.
  • Journal of  Algorithm and Computational Technology (JACT).
  • Journal of Theoretical and Applied Electronic Commerce (JTAER).
  • Journal of Electronic Commerce Research and Applications (ECRA).
  •  Journal of Trust Management.
  • Communication of the ACM.
  • Journal of Computational Intelligence.


  • President of Graduate Student Association in (CS-GSA) of the Faculty of Computer Science at University of New Brunswick, 2011-2012.
  • Representative of the Graduate Student Association in (CS-GSA) of the Faculty of Computer Science at University of New Brunswick, 2008-2011.
  • Graduate student peer mentor of the faculty of computer science, 2011-2013.
  • Student Volunteer Program in Canadian Conference of Artificial Intelligence, 2010.
  • Student Volunteer Program in 10th international  conference on Autonomous agents and Multiagent systems (AAMAS’11), 2011.


Graduate courses

  • Lecturer, Advanced Topic on Information Systems, University of Science and Technology, Winter 2015.
  • Lecturer, Research Method, University of Science and Technology, Winter 2015.

Undergraduate courses

  • Guest Lecturer, Social Computing, University of Saskatchewan, Fall 2014.
  • Teacher Assistant, Introduction to Object Oriented Programming in Java, University of New Brunswick, Fall and Winter 2012.
  • Teacher Assistant, Introduction to Computer Science and Programming, University of New Brunswick, Fall 2011.
  • Teacher Assistant, Advanced Java Programming, University of New Brunswick, Winter 2010.
  • Teacher Assistant, Programming Languages, University of New Brunswick, Fall 2009.
  • Teaching Assistant, Introduction to Artificial Intelligence, University of Science and Technology, Fall 2004.