Analyzing Customer Behavior Using Online Analytical Mining (OLAM)

ثبت نشده
چکیده

Online Analytical Mining (OLAM) is an architecture integrating data mining into OLAP. With this integration, data mining algorithms can be performed with OLAP abilities. OLAM enables users to choose a particular portion of data and analyze them with data mining models. Previous studies have provided examples of OLAM applications with the motivation to improve technical performance. This chapter reviews the capabilities of OLAM and discusses the well-known concept encompassing the analysis of customer behavior. The underlying motivation of this chapter is to present the opportunities for the development of OLAM to support the customer behavior analysis. Three main directions of the advancement in OLAM are proposed for future research.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Analyzing Customer Behavior Using Online Analytical Mining (OLAM)

Online Analytical Mining (OLAM) is an architecture integrating data mining into OLAP. With this integration, data mining algorithms can be performed with OLAP abilities. OLAM enables users to choose a particular portion of data and analyze them with data mining models. Previous studies have provided examples of OLAM applications with the motivation to improve technical performance. This chapter...

متن کامل

Analyzing Customer Behavior Using Online Analytical Mining (OLAM)

Online Analytical Mining (OLAM) is an architecture integrating data mining into OLAP. With this integration, data mining algorithms can be performed with OLAP abilities. OLAM enables users to choose a particular portion of data and analyze them with data mining models. Previous studies have provided examples of OLAM applications with the motivation to improve technical performance. This chapter...

متن کامل

An Olam Approach to Analyze E-commerce Clickstreams

Clickstream analysis can reveal usage patterns on the company’s web site and give highly improved understanding of customer behavior. This understanding can then be utilized for improving customer satisfaction with the website and the company in general, yielding a great business advantage. Such summary information and rules have to be extracted from very large collections of clickstreams in we...

متن کامل

An e-customer behavior model with online analytical mining for internet marketing planning

In the digital market, attracting sufficient online traffic in a business to customer Web site is vital to an online business’s success. The changing patterns of Internet surfer access to e-commerce sites pose challenges for the Internet marketing teams of online companies. For e-business to grow, a system must be devised to provide customers’ preferred traversal patterns from product awareness...

متن کامل

Customer behavior mining based on RFM model to improve the customer relationship management

Companies’ managers are very enthusiastic to extract the hidden and valuable knowledge from their organization data. Data mining is a new and well-known technique, which can be implemented on customers data and discover the hidden knowledge and information from customers' behaviors. Organizations use data mining to improve their customer relationship management processes. In this paper R, F, an...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2015