Identifying Buying Patterns from Consumers’ Purchase History Using Big Data and Cloud Computing

2021 ◽  
Author(s):  
Hui Zhang
Keyword(s):  
Decision Making ◽  
Cloud Computing ◽  
Big Data ◽  
Consumer Behavior ◽  
Global Marketplace ◽  
Customer Preference ◽  
Second Stage ◽  
Two Stages ◽  
Brand Consistency ◽  
Research Analysis

Consumers can select their goods and resources in several ways, significantly affecting customer preference in the online world and raising network customers’ demands to anticipate their purchasing pattern. The current work aims to identify buying patterns from consumers’ purchase history (IBP-CPH) framework for analyzing the evolving trend of customer decision-making in the global marketplace. The project is carried out in two stages to achieve the goals. A comprehensive research analysis is conducted to evaluate the latest consumer behavior trends in the digital economy in this first stage. In the second stage, identifying buying patterns from consumers’ purchase history (IBP-CPH) framework identifies the finalized factor’s preference amounts (s). The concept of a fugitive setting requires the incoherence of information to be recorded. The results achieved in this research stated that buyers are very aware of new and sophisticated brands and brand consistency so that internet companies can keep their customers on their web platforms.

Integrated Model for MCDM: Selection Contractor in Malaysian Construction Industry

2014 ◽  
Vol 548-549 ◽  
pp. 1587-1595
Author(s):  
Waled Alzober ◽  
Abdul Razak Yaakub
Keyword(s):  
Decision Making ◽  
Construction Industry ◽  
Construction Projects ◽  
Integrated Model ◽  
Decision Making Process ◽  
Contractor Selection ◽  
Second Stage ◽  
Proposed Model ◽  
Two Stages ◽  
Selection Of

A complex or unstructured problem is based on multi criteria not on a single criterion. A contractor selection problem is a multi-criteria problem. A correct decision-making is required for selecting the appropriate contractor for a construction project. Selection of a contractor is a key decision made by clients and the process of selection a contractor has become an important issue in construction projects. Many multi-criteria techniques have been proposed and applied to such problems solution. This paper aims to propose integrated model for MCDM. The integrated model contains two stages. First stage integrates two MCDM methods are AHP and ANN to prepare a shortlist of the best alternatives. Second stage apply statistical model COP to choose the optimum alternative from the best alternatives in a shortlist. Proposed model for tendering system provides automated a decision-making process that reduces the time and manpower requirements for processing tender

Results of first stage brachiobasilic and brachiobrachial fistula creation: Implications for staged versus single procedure decision making

2021 ◽  
pp. 112972982110052
Author(s):  
Mary Ottinger ◽  
Desiree Picone ◽  
Katrina Hseih ◽  
Mathew Wooster ◽  
Mark J London ◽  
...  
Keyword(s):  
Decision Making ◽  
Operating Room ◽  
Senior Author ◽  
Two Stage ◽  
Second Stage ◽  
Single Procedure ◽  
Av Fistulas ◽  
Two Stages ◽  
Lost To Follow Up

Introduction: Transposed brachiobasilic AV fistulas (BVT) have increasingly been performed in two stages. Published reports give conflicting results, perhaps in part as many reports of staged procedures eliminate those patients who “fail” the first stage (i.e. are lost to follow-up in addition to anatomic failure). Methods: A prospectively maintained database was reviewed to identify all patients at two institutions who underwent the first stage of planned two-stage BVT by the senior author. Success in this context was defined as patients who eventually underwent second stage fistula creation, leaving the operating room after the second stage with a patent, transposed fistula. Results: From October 2012 to June 2020, 218 patients underwent first-stage procedures. At the first visit, 185 (85%) of fistulas were patent, 23 (11%) were occluded, 8 (4%) of patients were lost to follow-up, and 2 (1%) died. In the interval before the second operation, another eight (4%) patients were lost to follow-up, two were cancelled for medical reasons, and two declined surgery, leaving a total of 173 patients who made it to the second stage (80%). At operation, four patients were found to have unusable veins, leaving a total of 169 patients who completed both stages. If all patients who underwent first stage are included, 77% of patients entering this pathway left the OR after their second stage with patent access. If those lost to follow-up are excluded, this number increases to 84%, while if all those lost to follow-up are assumed to mature, success increases to 85%. Conclusions: Depending on results in patients lost to follow-up, between 77% and 85% of patients undergoing first stage brachiobasilic fistulae undergo successful second stage transposition. These numbers are equivalent or slightly lower than published maturation rates for single-stage BVT, so there is little margin for failure at the second stage.

scholarly journals A Patent Analysis on Big Data Projects

2022 ◽  
Vol 9 (1) ◽  
pp. 1-14
Author(s):  
Gustavo Grander ◽  
Luciano Ferreira da Silva ◽  
Ernesto D. R. Santibanez Gonzalez
Keyword(s):  
Decision Making ◽  
Cloud Computing ◽  
Big Data ◽  
Internet Of Things ◽  
Academic Research ◽  
Data Driven ◽  
The Internet ◽  
Word Classes ◽  
Patent Documents ◽  
The Internet Of Things

Studies concerning Big Data patents have been published; however, research investigating Big Data projects is scarce. Therefore, the objective of this study was to conduct an exploratory analysis of a patent database to collect information about the characteristics of registered patents related to Big Data projects. We searched for patents related to Big Data projects in the Espacenet database on January 10, 2021, and identified 109 records.. The textual analysis detected three word classes interpreted as (i) a direction to cloud computing, (ii) optimization of solutions, and (iii) storage and data sharing structures. Our results also revealed emerging technologies such as Blockchain and the Internet of Things, which are utilized in Big Data project solutions. This observation demonstrates the importance that has been given to solutions that facilitate decision-making in an increasingly data-driven context. As a contribution, we understand that this study endorses a group of researchers that has been dedicated to academic research on patent documents.

scholarly journals The Deep Learning and Apache Spark Enabled Architecture for Improving the Performance of Big Data Classification

2019 ◽  
Vol 8 (11) ◽  
pp. 2908-2914
Keyword(s):  
Big Data ◽  
Deep Learning ◽  
Review Paper ◽  
Data Classification ◽  
Apache Spark ◽  
The Novel ◽  
Second Stage ◽  
Big Data Applications ◽  
Big Data Classification ◽  
Two Stages

At present the Big Data applications, for example, informal communication, therapeutic human services, horticulture, banking, financial exchange, instruction, Facebook and so forth are producing the information with extremely rapid. Volume and Velocity of the Big information assumes a significant job in the presentation of Big information applications. Execution of the Big information application can be influenced by different parameters. Expediently search, proficiency and precision are the a portion of the overwhelming parameters which influence the general execution of any Big information applications. Due the immediate and aberrant inclusion of the qualities of 7Vs of Big information, each Big Data administrations anticipate the elite. Elite is the greatest test in the present evolving situation. In this paper we propose the Big Data characterization way to deal with speedup the Big Data applications. This paper is the review paper, we allude different Big information advancements and the related work in the field of Big Data Classification. In the wake of learning and understanding the writing we discover the holes in existing work and techniques. Finally we propose the novel methodology of Big Data characterization. Our methodology relies on the Deep Learning and Apache Spark engineering. In the proposed work two stages are appeared; first stage is include choice and second stage is Big Data Classification. Apache Spark is the most reasonable and predominant innovation to execute this proposed work. Apache Spark is having two hubs; introductory hubs and last hubs. The element choice will be occur in introductory hubs and Big Data Classification will happen in definite hubs of Apache Spark

Balancing Exploration and Exploitation Through Customer Development Model

2021 ◽  
pp. 839-852
Author(s):  
Krishna Raj Bhandari
Keyword(s):  
Artificial Intelligence ◽  
Decision Making ◽  
Cloud Computing ◽  
Big Data ◽  
Internet Of Things ◽  
Best Practices ◽  
Industry 4.0 ◽  
Development Model ◽  
Exploration And Exploitation ◽  
Customer Development

Balancing exploration and exploitation in entrepreneurial ventures enabled by Industry 4.0 has not been the focus of the existing literature. It is because the phenomenon is emerging and the focus has been to use practitioners' best practices in studying such phenomenon. In this chapter, the author combines the literature in balancing exploration and exploitation with the practitioners' best practices such as customer development model and lean startup. The author proposes that the existing models are good in principle but in order to really solve the problem in such an uncertain environment driven by big data, cloud computing, internet of things (IoT), and artificial intelligence, managers need to embed optimization algorithms in their decision making.

How the ANES Used Online Commons Proposals and Pilot Study Reports to Develop Its 2008 Questionnaires

2011 ◽  
Author(s):  
Jon A. Krosnick ◽  
Arthur Lupia
Keyword(s):  
Decision Making ◽  
Pilot Study ◽  
General Election ◽  
Large Set ◽  
The Public ◽  
Second Stage ◽  
Decision Making Processes ◽  
Two Stages

This chapter describes the manner by which the ANES converted the insights of many people into strong and innovative questionnaires. This description is broken into two stages to reflect the nature of the decision-making processes. The first stage began in 2006, two years before the general election of 2008. The chapter describes how a large set of new questions were evaluated and which questions were to be included in the 2006 Pilot Study. The second stage began about six weeks after the pilot study, when the data was released to the public. This period started at the end of 2006 and continued into the early months of 2008. The chapter looks at how the Pilot Study Reports from the period were evaluated and how these evaluations affected choices of which questions would appear on one or more of the 2008 studies.

scholarly journals Data Mining and Knowledge Discovery for Big Data in Cloud Environment

Webology ◽  
2021 ◽  
Vol 18 (Special Issue 04) ◽  
pp. 1118-1131
Author(s):  
Raid Abd Alreda Shekan ◽  
Ahmed Mahdi Abdulkadium ◽  
Hiba Ameer Jabir
Keyword(s):  
Data Mining ◽  
Decision Making ◽  
Cloud Computing ◽  
Big Data ◽  
Large Data ◽  
Cloud Computing Environment ◽  
New Methods ◽  
History Of ◽  
New Vision ◽  
Digital Processes

In past few decades, big data has evolved as a modern framework that offers huge amount of data and possibilities for applying and/or promoting analysis and decision-making technologies with unparalleled importance for digital processes in organization, engineering and science. Because of the new methods in these domains, the paper discusses history of big data mining under the cloud computing environment. In addition to the pursuit of exploration of knowledge, Big Data revolution gives companies many exciting possibilities (in relation to new vision, decision making and business growths strategies). The prospect of developing large-data processing, data analytics, and evaluation through a cloud computing model has been explored. The key component of this paper is the technical description of how to use cloud computing and the uses of data mining techniques and analytics methods in predictive and decision support systems.

scholarly journals Risks of private investors in financing housing construction

2021 ◽  
pp. 245-254
Author(s):  
Natalia Sokolova ◽  
◽  
Bogdan Yatsenko ◽  
Vladimir Petrovich ◽  
Olena Usychenko ◽  
...  
Keyword(s):  
Decision Making ◽  
Control System ◽  
Investment Project ◽  
Housing Construction ◽  
Second Stage ◽  
Investment Object ◽  
Private Investors ◽  
Two Stages ◽  
Project Initiator

In public are considered the functioning features of mechanism of financing of housing construction through the Construction Financing Fund (CFF), the main investor risks of using CFF and pre-conditions of their origins are defined. It is educed that decision-making about investing using CFF must consist of two stages: on the first stage a bailiff chooses an investment project, initiator and proprietor the Builder, on the second stage the choice of object of investing is made by investor. The principles of choice and the model of choosing the Builder by bailiff are developed; the principles, model and methods of Investor's choice of investment object are offered. The control system was developed to monitor the pre- conditions of risk origins. The suggestions of legislative base improvements in relation to CFF are developed to decrease the risks of investors.

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