It is a challenge to visualize high dimensional data such as project  data to yield new and interesting types of insights. To address this, we augment the traditional PERT network diagram with additional nodes that represent resources, and with arcs from the resource nodes to the activities that use those resources. Subsequently, we apply various graph layout algorithms that can reveal the hidden patterns in the graph data. Finally, we also map various attributes of the activities to the features of activity nodes. We illustrate the applicability and usefulness of our methodology through two case studies, where we visualize data from a benchmark data library and from the real world.

Ertek, G., Choi, B.-G., Chi, X., Yang, D., Yong, O. B., “Graph-based analysis of resource dependencies in project networks”. In Proceedings of 2015 IEEE International Conference on Big Data (Big Data). (2015) 2143 – 2149.

Note: This is the final draft version of this paper. Please cite this paper (or this final draft) as above.

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Graph-Based Analysis of Resource Dependencies in Project Networks

Dr. Gürdal Ertek recommends the following related books:

Information Visualization: An Introduction, 3rd Ed. 2014 Edition

Network Flows: Theory, Algorithms, and Applications 1st Edition

Project Management: A Systems Approach to Planning, Scheduling, and Controlling

 

 

 

 

 

It is a challenge to estimate expected benefits from recommender systems based on association rule mining. This paper aims to address this challenge and presents a study of buying preferences of a sample of retail customers. It reveals a monotonic, non-linear relationship between the expected profits (as a function of information loss) and minimum support threshold levels, when considering transactions for a recommender system based on association rules. This finding is significant for recommender systems that utilize potential profits as a decision-making criterion.

Ertek, G., Chi, X., Yee, G., Yong, O. B., Choi, B.-G., “Profit Estimation Error Analysis in Recommender Systems based on Association Rules”. In Proceedings of 2015 IEEE International Conference on Big Data (Big Data). (2015) 2138 – 2142.

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Profit Estimation Error Analysis in Recommender Systems based on Association Rules

Dr. Gürdal Ertek recommends the following related books:

Information Visualization: An Introduction by Robert Spence (2014-11-04)

 

 

 

 

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The main purpose of this paper is to frame the perception differences between the buyer and supplier on the supply chain’s operational delivery, and to investigate their causal relation to the overall supply chain performance. A conceptual three-level model is developed to theorise the structural existence of the perception gaps in primarily a dyadic buyer-supplier setting. Using the primary data gathered through a major survey exercise, confirmative factor analysis and structural equation modelling were conducted to test the hypotheses on the significance and relevance of the perception gaps in supply chain management. This study provides a better conceptual understanding of the perception differences on the required as well as achieved operational deliveries within the supplier-buyer dyad, and reveals their significant and negative causal impact on the overall supply chain performance.

Lu, D., Ertek, G., (2015) “Perception gap and its impact on supply chain performance”, Int. J. Business Performance and Supply Chain Modelling, Vol. 7, No. 2, 122-140.

Dr. Gürdal Ertek recommends the following related books:

Operations and Supply Chain Management (Mcgraw-hill Education)

Information Visualization: An Introduction by Robert Spence (2014-11-04)