Application of Data Mining Methods for Pattern Recognition in Negotiation Support Systems

Kaya, Muhammed-Fatih; Schoop, Mareike

doi:10.1007/978-3-030-21711-2_17

Cited by 6 publications

(2 citation statements)

References 23 publications

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“…The term "Data Mining" was first registered for the 2010 Medical Subject Headings (Yoo et al, 2012). Data mining has been used for pattern recognition (Kaya & Schoop, 2019), database design (Chaudhuri, 1998), artificial intelligence (Navale et al, 2016), visualization, and applications in healthcare (Tomar & Agarwal, 2013). One of the definitions mostly used states that "data mining is the analysis of observational data sets to summarize the data in novel ways and to find unsuspected relationships that are both useful and understandable to the data owner" (Hand et al, 2001).…”

Section: Data Mining: Clustering Methods and Internal Validationmentioning

confidence: 99%

Care process optimization in a cardiovascular hospital: an integration of simulation–optimization and data mining

et al. 2022

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To provide health services, hospitals consume electrical power and contribute to the CO2 emission. This paper aims to develop a modelling approach to optimize hospital services while reducing CO2 emissions. To capture treatment processes and the production of carbon dioxide, a hybrid method of data mining and simulation–optimization techniques is proposed. Different clustering algorithms are used to categorize patients. Using quality indicators, clustering methods are evaluated to find the best cluster sets, and then patients are categorized accordingly. Discrete-event simulation is applied to each patient category to estimate performance measures such as number of patients being served, waiting times, and length of stay, as well as the amount of CO2 emission. To optimize performance measures of patient flow, metaheuristic searches have been used. The dataset of Bushehr Heart Hospital is considered as a case study. Based on K-means, K-medoid, Hierarchical clustering, and Fuzzy C-means clustering methods, patients are categorized into two groups of high-risk and low-risk patients. The number of patients being served, total waiting time, length of stay, and CO2 emitted during care processes are improved for both groups. The proposed hybrid method is an effective method for hospitals to categorize patients based on care processes. The problems and the proposed solution approach reported in this study could be applicable to other hospitals, worldwide to help both optimize the patient flow and minimize the environmental consequences of care services.

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Section: Data Mining: Clustering Methods and Internal Validationmentioning

confidence: 99%

Care process optimization in a cardiovascular hospital: an integration of simulation–optimization and data mining

et al. 2022

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“…We know, as humans, how to recognize emotions by facial expression; indeed, studies are dating back two decades for developing computer systems able to obtain high validity in this analysis of images based on facial muscle actions, and machine learning is further reinforcing this aspect (De Silva et al, 1997;Wingenbach et al, 2016, Abdulsalam et al, 2019 There is exciting research about how negotiation and emotions could be crossed in order to support this process (Broekens et al, 2010); indeed, decision making is influenced not only by rational analysis but also by current status, stress, and emotions as well as by the background and attitude of the parties. In this sense, some potential models could develop a negotiation support system; obviously, it is fundamental to have valid data related to the specific subject and negotiation of interest (Kaya & Schoop, 2019).…”

Section: Human Behavior and Profiling Attitudesmentioning

confidence: 99%

Data Value as the basis for Human Behavior Modeling

Bruzzone¹,

Longo²,

Franzinetti³

et al. 2021

Proceedings of the 23rd International Conference on Harbor, Maritime and Multimodal Logistic Modeling &Amp; Simulation

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This paper introduces the importance of creating models to evaluate the value of data regarding their potential to extract information to identify human behaviors, attitudes, and characteristics. This is just a preliminary overview on this potential and consider that in the future, these values could become parts of the assets of companies if properly acquired and processed in order to respect all regulations and all rights of all the parties.

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Negotiation communication revisited

Schoop

2021

Cent Eur J Oper Res

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Negotiators communicate with each other and decide on offers or requests. Whilst the decision side of negotiations has long been a focus of negotiation research, the communication side has not been extensively supported. The current paper revisits the need for a communication perspective in business negotiations and reviews current research on negotiation communication. Both strands of relevant work are then integrated to provide a concept of electronic negotiation communication and to discuss how this concept was implemented in the system Negoisst and thus operationalised.

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Application of Data Mining Methods for Pattern Recognition in Negotiation Support Systems

Cited by 6 publications

References 23 publications

Care process optimization in a cardiovascular hospital: an integration of simulation–optimization and data mining

Care process optimization in a cardiovascular hospital: an integration of simulation–optimization and data mining

Data Value as the basis for Human Behavior Modeling

Negotiation communication revisited

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