@inproceedings{davoust_user_2016,

title = {User participation and honesty in online rating systems: What a social network can do},

author = {A. Davoust and B. Esfandiari},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85021919921&partnerID=40&md5=6a33a1ab6d3b6ddd037240f4f664b6fe},

isbn = {978-1-57735-759-9},

year  = {2016},

date = {2016-01-01},

booktitle = {AAAI Workshop - Technical Report},

volume = {WS-16-01 - WS-16-15},

pages = {477–483},

publisher = {AI Access Foundation},

abstract = {An important problem with online communities in general, and online rating systems in particular, is uncooperative behavior: lack of user participation, dishonest contributions. This may be due to an incentive structure akin to a Prisoners' Dilemma (PD). We show that introducing an explicit social network to PD games fosters cooperative behavior, and use this insight to design a new aggregation technique for online rating systems. Using a dataset of ratings from Yelp, we show that our aggregation technique outperforms Yelp's proprietary filter, as well as baseline techniques from recommender systems. Copyright © 2016, Association for the Advancement of Artificial Intelligence (www.aaai.org).},

keywords = {Aggregation techniques, Artificial intelligence, Behavioral research, Big data, Co-operative behaviors, Cognitive systems, Computer games, Computer programming, Computer systems programming, Data mining, Hybrid systems, Incentive structure, On-line communities, Online rating systems, Online systems, Population statistics, Prisoners' Dilemma, Rating, Social networking (online), User participation},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{nabelsi_detecting_2015,

title = {Detecting constraints in supply chain reengineering projects: Case study of data and process integration in a hospital pharmacy},

author = {V. Nabelsi and S. Gagnon},

editor = {Zaremba M. Sasiadek J. Dolgui A.},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84953887968&doi=10.1016%2fj.ifacol.2015.06.066&partnerID=40&md5=ce9be2cbe2fdcfc4872793c13f4228a2},

doi = {10.1016/j.ifacol.2015.06.066},

isbn = {24058963 (ISSN)},

year  = {2015},

date = {2015-01-01},

booktitle = {IFAC-PapersOnLine},

volume = {28},

pages = {106–111},

abstract = {This paper discusses how messy data may be a hidden failure factor that Business Process Reengineering (BPR) projects typically cannot detect during the planning phase. Our case study deals with Supply Chain Management (SCM) within two major urban hospitals, involving $2 million in minimum stocks for drug inventory. Our project addresses the feasibility of the hospital's data warehousing integration, especially at the stage of Extract, Transform, and Load (ETL). We conclude with a proposed system architecture audit and verification method that may serve to guide reengineering project planning and execution. © 2015, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.},

note = {Issue: 3 

Journal Abbreviation: IFAC-PapersOnLine},

keywords = {Administrative data processing, Artificial intelligence, Business Process, Business process management, Business process management (BPM), Business process re-engineering, Case-studies, Data integration, Data mining, Data models, Data structures, Data warehouses, Decision support system, Decision support system (dss), Decision support systems, Enterprise resource management, Extract transform and load, Extract Transform and Load (ETL), Hospitals, Information management, Integration, Process management, Project case, Re-engineering projects, Reengineering, Supply chain management, Supply Chain Management (SCM), Supply chain managements (SCM), System architectures, Verification method, Verification of information system},

pubstate = {published},

tppubtype = {inproceedings}

}