نتایج جستجو برای: customer clustering analysis
تعداد نتایج: 2896338 فیلتر نتایج به سال:
Swarm Intelligence (SI) is an innovative artificial intelligence technique for solving complex optimization problems. Data clustering is the process of grouping data into a number of clusters. The goal of data clustering is to make the data in the same cluster share a high degree of similarity while being very dissimilar to data from other clusters. Clustering algorithms have been applied to a ...
Data clustering consists in finding homogeneous groups in a dataset. According to their own experience and background, many eminent Authors have proposed different definitions for data clustering. Here we propose a very general one that can cover almost all the data clustering approaches. Given a set of n points in a p dimensional space, cluster analysis aims at grouping data into k groups that...
Data clustering is a common technique for statistical data analysis, which is used in many fields, including machine learning, data mining, customer segmentation, trend analysis, pattern recognition and image analysis. Although many clustering algorithms have been proposed most of them deal with clustering of numerical data. Finding the similarity between numeric objects usually relies on a com...
due to extraordinary large amount of information and daily sharp increasing claimant for ui benefits and because of serious constraint of financial barriers, the importance of handling fraud detection in order to discover, control and predict fraudulent claims is inevitable. we use the most appropriate data mining methodology, methods, techniques and tools to extract knowledge or insights from ...
Personalized recommendation systems can help people to find interesting things and they are widely used with the development of electronic commerce. Many recommendation systems employ the collaborative filtering technology, which has been proved to be one of the most successful techniques in recommender systems in recent years. With the gradual increase of customers and products in electronic c...
Data clustering is a common technique for statistical data analysis. It is used in many fields including machine learning, data mining, customer segmentation, trend analysis, pattern recognition and image analysis. The proposed Localized Diffusion Folders methodology performs hierarchical clustering and classification of high-dimensional datasets. The diffusion folders are multi-level data part...
The hospitality industry is one of the data-rich industries that receives huge Volumes of data streaming at high Velocity with considerably Variety, Veracity, and Variability. These properties make the data analysis in the hospitality industry a big data problem. Meeting the customers' expectations is a key factor in the hospitality industry to grasp the customers' loyalty. To achieve this goal...
Product configuration design is of critical importance in design for mass customization. This paper will investigate two important issues in configuration design. The first issue is requirement configuration and a dependency analysis approach is proposed and implemented to link customer groups with clusters of product specifications. The second issue concerns the engineering configuration and i...
this study considers the level of increase in customer satisfaction by supplying the variant customer requirements with respect to organizational restrictions. in this regard, anp, qfd and bgp techniques are used in a fuzzy set and a model is proposed in order to help the organization optimize the multi-objective decision-making process. the prioritization of technical attributes is the result ...
This research establishes a dynamic game-theoretic model that interprets the mechanism of reputation feedback systems in online consumer-to-consumer (C2C) auction markets. Based on the model, a numerical study is conducted to reveal the effects of feedback systems on auction markets. The study shows that the existence of feedback systems greatly improves the performance of online C2C auction ma...
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