We consider a simple model of unreliable or crowdsourced data where there is an underlying set of n binary variables, each “evaluator” contributes a (possibly unreliable or adversarial) estimate of the values of some subset of r of the variables, and the learner is given the true value of a constant number of variables. We show that, provided an α-fraction of the evaluators are “good” (either c...

While customizing their products, manufacturers attempt to ful ll speci c requirements of the customers within the constraints dictated by the manufacturing (design, planning and production) environment, and by the economical necessity of earning pro t. This paper o ers a generic framework that captures more technical features of this problem than the marketing models: in addition to customer w...

Customer satisfaction is an integral component of any successful business. It vital for companies to understand the needs and preferences their customers ensure long-term success. The aim this study measure customer with special reference Coffee Cafe Day in Pune city. will investigate factors that influence identify areas improvement service.

This paper examines whether customer use of virtual channels varies with the type of service activities (e.g. information search, transactions) they engage in. Based on data from a multichannel bank, we first investigate the impact of customer distance to the nearest branch on the degree of use of virtual channels (internet and phone, aggregated), for different types of activities. Second, when...

Customer clustering is used to understand customers’ preferences and behaviors by examining the differences and similarities between customers. Kohonen vector quantization clustering technology is used in this research and is compared with Kmeans clustering. The data set consists of customer records obtained from a mobile telecommunications service provider. The customers are clustered using va...

With hundreds, even thousands, of hotels to choose from at every destination, it's difficult to know which will suit your personal preferences. Expedia wants to take the proverbial rabbit hole out of hotel search by providing personalized hotel recommendations to their users. This is no small task for a site with hundreds of millions of visitors every month! Currently, Expedia uses search p...

Increasing occupancy rates and revenue by improving customer experience is the aim of modern hospitality organizations. To achieve these results, hotel managers need to have a deep knowledge of customers’ needs, behavior, and preferences and be aware of the ways in which the services delivered create value for the customers and then stimulate their retention and loyalty. In this article a metho...

Today with the advent of technology data has expanded to the size of millions of terabytes. For retail industries, customer’s data works as tracks for analysing their buying behaviour. How this data is maintained and used for an effective decision making in retail industry is discussed in this paper. This not only increases profit for companies but also poses a challenge in the field of data mi...

We discuss a semantic platform that matches a customer’s purchase intent against vendor offers. The customers’ perception on particular products, including evolving needs and preferences, were captured in a request and product ontology, in turn used to annotate vendor offers. During the project, however, we observed an important gap between the intent descriptions of users and the available dat...

The success of a business process (BP) depends on whether it meets its business goal as well as non-functional requirements associated with it. BP specifications frequently need to accommodate changing business priorities, varying client preferences, etc. However, since business process goals and preferences are rarely captured explicitly in the dominant BP modeling approaches, adapting busines...