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Titlebook: Business and Consumer Analytics: New Ideas; Pablo Moscato,Natalie Jane de Vries Book 2019 Springer Nature Switzerland AG 2019 Customer ana

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發(fā)表于 2025-3-21 17:50:53 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
期刊全稱Business and Consumer Analytics: New Ideas
影響因子2023Pablo Moscato,Natalie Jane de Vries
視頻videohttp://file.papertrans.cn/193/192463/192463.mp4
發(fā)行地址An influential approach towards interdisciplinary work; bringing new computer science approaches to social science applications.First of its kind in the area of novel ideas in consumer analytics invol
圖書封面Titlebook: Business and Consumer Analytics: New Ideas;  Pablo Moscato,Natalie Jane de Vries Book 2019 Springer Nature Switzerland AG 2019 Customer ana
影響因子.This two-volume handbook presents a collection of novel methodologies with applications and illustrative examples in the areas of data-driven computational social sciences. Throughout this handbook, the focus is kept specifically on business and consumer-oriented applications with interesting sections ranging from clustering and network analysis, meta-analytics, memetic algorithms, machine learning, recommender systems methodologies, parallel pattern mining and data mining to specific applications in market segmentation, travel, fashion or entertainment analytics. A must-read for anyone in data-analytics, marketing, behavior modelling and computational social science, interested in the latest applications of new computer science methodologies..The chapters are contributed by leading experts in the associated fields.The chapters cover technical aspects at different levels, some of which are introductory and could be used for teaching. Some chapters aim at building a commonunderstanding of the methodologies and recent application areas including the introduction of new theoretical results in the complexity of core problems.? Business and marketing professionals may use the book to f
Pindex Book 2019
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https://doi.org/10.1007/978-3-540-74925-7st important nodes in networks. The idea is to define a centrality measure for each node in the network, sort the nodes according to their centralities, and fix our attention to the first ranked nodes, which can be considered as the most relevant ones with respect to this centrality measure.
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發(fā)表于 2025-3-22 05:54:04 | 只看該作者
https://doi.org/10.1007/978-3-662-08644-5a large number of problem domains. This work gives a historical timeline of events to explain the current developments and, as a survey, gives emphasis to the large number of applications in business and consumer analytics that were published between January 2014 and May 2018.
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Memetic Algorithms for Business Analytics and Data Science: A Brief Surveya large number of problem domains. This work gives a historical timeline of events to explain the current developments and, as a survey, gives emphasis to the large number of applications in business and consumer analytics that were published between January 2014 and May 2018.
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發(fā)表于 2025-3-23 07:04:12 | 只看該作者
A Memetic Algorithm for the Team Orienteering Problemfor solving the TOP. The concept of the “similarity operator” is that feasible sub-routes of the solutions are serving as chromosomes. The efficacy of . was tested using the knownbenchmark instances for the TOP. From the experiments it was concluded that “similarity operator” is a promising technique and . produces quality solutions.
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