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Category Archives: Case Studies
Challenge March-2019 “Organ Transplant Decisioning”
The development of techniques for organ transplant means that now one person’s death may lead to a lifesaving operation for another. This challenge considers one of the many crucial decision-making processes involved in this miracle of modern medicine. Possible solutions to … Continue reading
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DMN for Clinical Decision Support
Can DMN be used for creating shareable knowledge artifacts for Clinical Decision Support (CDS)? This paper considers different options. “If so, then we can take advantage of many of the DMN tools to author knowledge artifacts and implement CDS services … Continue reading
Posted in Case Studies, DMN, Uncategorized
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Business Rules Excellence Awards
Do you have an interesting Business Rules Use Case? Submit it for the opportunity to win a highly prestigious award and publication in the next book on BR to be published within 12 months following the Awards Ceremony at BBC-2018. The Business Rules Excellence … Continue reading
Posted in Case Studies, Misc, Rule Engines and BRMS
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Decision Model for Order Promotions
Our Jan-2018 Challenge deals with a popular business decision problem: help merchants to define various promotions for their sales orders and to automatically decide which orders are eligible to which promotions. A simple example of promotion: reduce the total cost of … Continue reading
Posted in Case Studies, Challenges, Decision Modeling, Decision Models, DMN
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Best Challenges/Solutions of 2017: Poll Results
We received 91 votes for our 2017 Community poll. The challenges/solutions which collected the most votes are presented in the following table: As all votes were anonymous, it’s hard to tell how objective these results are: we do not know … Continue reading
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Detecting Serial Killers with Data
The New Yorker’s article “The Serial-Killer Detector” describes how an algorithm is discovering new links between unsolved murders. By a process of data aggregating, the algorithm gathers killings that are related by method, place, and time, and by the victim’s sex. … Continue reading
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Recommender Engine – Under The Hood
There are two types of recommender systems, Content based and Collaborative filtering. Both have their pros and cons depending upon the context in which you want to use them. This article describes how to build a content-based recommender system.
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