標(biāo)題: Titlebook: Business and Consumer Analytics: New Ideas; Pablo Moscato,Natalie Jane de Vries Book 2019 Springer Nature Switzerland AG 2019 Customer ana [打印本頁(yè)] 作者: calcification 時(shí)間: 2025-3-21 17:50
書(shū)目名稱(chēng)Business and Consumer Analytics: New Ideas影響因子(影響力)
書(shū)目名稱(chēng)Business and Consumer Analytics: New Ideas影響因子(影響力)學(xué)科排名
書(shū)目名稱(chēng)Business and Consumer Analytics: New Ideas網(wǎng)絡(luò)公開(kāi)度
書(shū)目名稱(chēng)Business and Consumer Analytics: New Ideas網(wǎng)絡(luò)公開(kāi)度學(xué)科排名
書(shū)目名稱(chēng)Business and Consumer Analytics: New Ideas被引頻次
書(shū)目名稱(chēng)Business and Consumer Analytics: New Ideas被引頻次學(xué)科排名
書(shū)目名稱(chēng)Business and Consumer Analytics: New Ideas年度引用
書(shū)目名稱(chēng)Business and Consumer Analytics: New Ideas年度引用學(xué)科排名
書(shū)目名稱(chēng)Business and Consumer Analytics: New Ideas讀者反饋
書(shū)目名稱(chēng)Business and Consumer Analytics: New Ideas讀者反饋學(xué)科排名
作者: ovation 時(shí)間: 2025-3-22 00:14 作者: 阻礙 時(shí)間: 2025-3-22 02:21
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.作者: Leisureliness 時(shí)間: 2025-3-22 05:54
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.作者: 外貌 時(shí)間: 2025-3-22 11:01 作者: abnegate 時(shí)間: 2025-3-22 13:37 作者: 榮幸 時(shí)間: 2025-3-22 20:38 作者: 包庇 時(shí)間: 2025-3-23 00:21 作者: 誘惑 時(shí)間: 2025-3-23 04:04
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.作者: 法律 時(shí)間: 2025-3-23 07:04
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.作者: Cabinet 時(shí)間: 2025-3-23 12:32 作者: regale 時(shí)間: 2025-3-23 17:37 作者: Water-Brash 時(shí)間: 2025-3-23 18:02
https://doi.org/10.1007/978-3-540-74925-7tem are determined only by their group memberships. The accurate prediction of individual user preferences over items can be accomplished by different methodologies, such as Monte Carlo sampling or Expectation-Maximization methods, the latter resulting in a scalable algorithm which is suitable for large datasets.作者: airborne 時(shí)間: 2025-3-24 00:35 作者: Customary 時(shí)間: 2025-3-24 02:48
Network-Based Models for Social Recommender Systemstem are determined only by their group memberships. The accurate prediction of individual user preferences over items can be accomplished by different methodologies, such as Monte Carlo sampling or Expectation-Maximization methods, the latter resulting in a scalable algorithm which is suitable for large datasets.作者: COLIC 時(shí)間: 2025-3-24 09:24 作者: 可觸知 時(shí)間: 2025-3-24 12:32
A Memetic Algorithm for Competitive Facility Location Problemsodels. We conclude this chapter with a case study for two hypermarket chains who both want to open stores in Vienna using real world demographic data. In this study we consider six different customer behaviour scenarios and present numerical and graphical results which show the effectiveness of the presented approach.作者: 聯(lián)想 時(shí)間: 2025-3-24 17:58 作者: 短程旅游 時(shí)間: 2025-3-24 20:11
Pablo Moscato,Natalie Jane de VriesAn 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作者: 比目魚(yú) 時(shí)間: 2025-3-25 02:48
http://image.papertrans.cn/b/image/192463.jpg作者: 協(xié)奏曲 時(shí)間: 2025-3-25 07:14
https://doi.org/10.1007/978-3-030-06222-4Customer analytics; Data science; Business analytics; Heuristics; Memetic algorithms; Network analysis; Da作者: CAJ 時(shí)間: 2025-3-25 11:34 作者: 蛙鳴聲 時(shí)間: 2025-3-25 12:44
https://doi.org/10.1007/978-3-662-12453-6asing availability of large volumes of data together with the advances in artificial intelligence, machine learning and optimization techniques. Breakthroughs in statistics, discrete applied mathematics and new algorithms are leading to the development of a new interdisciplinary field: data science.作者: 同音 時(shí)間: 2025-3-25 17:19
https://doi.org/10.1007/978-3-662-12453-6 needed in business and consumer analytics from a marketing perspective and continue “bridging the gap” between data scientists and business thinkers. A brief introduction to the discipline of marketing is presented followed by several topics that are crucial for understanding marketing and computat作者: 怪物 時(shí)間: 2025-3-25 22:06 作者: 天賦 時(shí)間: 2025-3-26 00:30
Biokompatible Keramische Werkstoffe has shown high scalability in previous applications, is applied to analyse and segment an online consumer behaviour dataset. It is based on the computation of a Minimum-Spanning-Tree and a .-Nearest Neighbour graph (MST-.NN). Cluster-specific consumer behaviours relating to customer engagement are 作者: 高爾夫 時(shí)間: 2025-3-26 05:52
Suk-Woo Ha,Michael Koller,Gerald G?llnerion and overview of basic sequential algorithms, and then discuss and compare different parallel approaches based on shared-memory, message-passing, map-reduce, and the use of GPU accelerators. Even though our survey certainly is not exhaustive, it covers essential reference material, since we belie作者: Anonymous 時(shí)間: 2025-3-26 11:27 作者: phase-2-enzyme 時(shí)間: 2025-3-26 15:10 作者: 懶惰民族 時(shí)間: 2025-3-26 19:28 作者: 輕快帶來(lái)危險(xiǎn) 時(shí)間: 2025-3-26 21:49
J. Blum,M. Petitmermet,E. Wintermantele not necessarily derived from the topology. Blind application of most graph drawing algorithms produces a “hairball” even for modest graph sizes. In this chapter, we explore several intuitive mechanisms to decompose a weighted graph into vertex clusters and edge layers that facilitate user explorat作者: 種植,培養(yǎng) 時(shí)間: 2025-3-27 02:01
https://doi.org/10.1007/978-3-540-74925-7ers. Recommender systems solve this problem by modelling and predicting individual preferences for a great variety of items such as movies, books or research articles. In this chapter, we explore rigorous network-based models that outperform leading approaches for recommendation. The network models 作者: 狼群 時(shí)間: 2025-3-27 06:02 作者: AER 時(shí)間: 2025-3-27 13:16
https://doi.org/10.1007/978-3-662-08644-5 address optimization problems that involve combinatorial search processes. Some of these problems were from the area of operations research, management science, artificial intelligence and machine learning. The methodology has developed considerably since its beginnings and now is being applied to 作者: noxious 時(shí)間: 2025-3-27 15:29 作者: COST 時(shí)間: 2025-3-27 21:21 作者: Foam-Cells 時(shí)間: 2025-3-28 00:30 作者: faddish 時(shí)間: 2025-3-28 02:22 作者: pacifist 時(shí)間: 2025-3-28 09:36 作者: Jacket 時(shí)間: 2025-3-28 11:49 作者: Left-Atrium 時(shí)間: 2025-3-28 17:13
Introducing Clustering with a Focus in Marketing and Consumer Analysisbe segmented, clustering methodologies are some of the most common ways of doing so nowadays. Clustering, however, is a hugely heterogeneous field in itself with advances and explanations coming from many different disciplines. Clustering has been discussed in debates almost as heated as those about作者: 倒轉(zhuǎn) 時(shí)間: 2025-3-28 18:57 作者: Hyperopia 時(shí)間: 2025-3-29 01:34
Frequent Itemset Miningion and overview of basic sequential algorithms, and then discuss and compare different parallel approaches based on shared-memory, message-passing, map-reduce, and the use of GPU accelerators. Even though our survey certainly is not exhaustive, it covers essential reference material, since we belie作者: Concerto 時(shí)間: 2025-3-29 06:25
Business Network Analytics: From Graphs to Supernetworksn in discrete applied mathematics and computer science. In many cases, they are the most natural means to represent some type of relationships in data. Consequently, a large number of solution methods based on heuristics and exact algorithms exist for problems that have graphs and/or networks as par作者: 注射器 時(shí)間: 2025-3-29 08:27 作者: Abnormal 時(shí)間: 2025-3-29 12:10
Overlapping Communities in Co-purchasing and Social Interaction Graphs: A Memetic Approachication networks, transportation routes and several others. An important feature of complex networks is the presence of communities, groups of elements densely connected among them but sparsely linked to the rest of the network. In many cases these communities can be overlapping, with nodes particip作者: 枯萎將要 時(shí)間: 2025-3-29 19:37 作者: medieval 時(shí)間: 2025-3-29 22:31 作者: Intersect 時(shí)間: 2025-3-30 02:30 作者: Tremor 時(shí)間: 2025-3-30 04:19 作者: gain631 時(shí)間: 2025-3-30 11:59
A Memetic Algorithm for the Team Orienteering Problem a score value. The goal of the TOP is to construct a discrete number of routes in order to visit the nodes and collect their scores aiming to maximize the total collected score with respect to a total travel time constraint. In this paper we propose a Memetic algorithm with Similarity Operator (.) 作者: FLUSH 時(shí)間: 2025-3-30 15:59 作者: 低三下四之人 時(shí)間: 2025-3-30 17:50 作者: opinionated 時(shí)間: 2025-3-30 23:29
Biokompatible Keramische Werkstoffe these clusters, a linear model of customer engagement was predicted using symbolic regression analysis. These models inform possible personalized marketing strategies after proper segmentation of the customers based on their online consumer behaviour, rather than simple demographic characteristics.
