Informatics Publishing Limited

Rafi Ahmad Khan ¹

Affiliations
1 Business School, University of Kashmir, IN

Abstract

Revolution of information technology in general and the World Wide Web in particular has created opportunity of building better relationships with customers. Until recently, simplifying the management and organization of customer information was main focus of Customer Relationship Management software's. Such software, called Customer Relationship Management, mainly focused on creating a database of customer's vital information. However, the sheer volumes of this customer information created need for organizations to look for methods and techniques to automatically and intelligently gain insight into customers and their needs through data analysis. Data Mining is popular means of analyzing large volumes of data in order to extract the valuable information/knowledge hidden in this data. There is an emerging trend of using data mining tools for Customer Relationship Management by the organizations in order to analyze and understand buying behavior of customers and their characteristics, so as to retain existing customers, acquire new potential customers and maximize their value. This paper presents concepts of Customer Relationship Management and Data Mining, framework of Customer Relationship Management and Data Mining, application of various data mining techniques in Customer Relationship Management.

Keywords

Customer Relationship Management (CRM), Data Mining (DM), Clustering, Association, Sequencing, Neural Networks, Regression.

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Rafi Ahmad Khan ¹

Affiliations
1 Business School, University of Kashmir, Srinagar, Jammu and Kashmir, IN

Abstract

Web mining is a newly emerging field and research area of data mining concerned with analyzing huge volume of data present on the World Wide Web. It is mainly concerned with web usage, web structure and web content. Web content mining lays emphasizes on the discovery/retrieval of the useful information from the Web content/Web documents/Web data, while the Web structure mining focuses on the discovery of how to model the underlying link structures of the web. Web usage mining mainly describes the techniques that discover the Web site visitor’s usage pattern and try to predict their behaviors. This paper discusses the web mining, its three categories and the applications of web mining in business.

Keywords

Web Mining, Web Usage, Web Structure, Web Content, Data Mining, Information Retrieval.

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Rafi Ahmad Khan ¹

Affiliations
1 Business School, University of Kashmir, Srinagar-190001, Jammu & Kashmir, IN

Abstract

Globalization, competition and the rapid advancements in ICT are driving unprecedented revolutionary changes in the way organizations do business. Consequently, business world is rapidly changing, with business processes becoming more and more complex, making it increasingly difficult for managers to have a comprehensive understanding of business environment. These factors have resulted in fast growing capabilities, both in generating as well as collecting data. In spite of having massive data, the organizations fail to completely exploit the real benefits which can be acquired from the great wealth of information hidden in this huge volume of data. One such technique which is finding increasing applications in business is data mining, the process of extracting hidden valuable information from the data in given data sets. Data mining tools are being used for marketing, customer profitability, customer segmentation and customer relationship management. This paper gives a brief insight about data mining, its process and the various techniques that can be used it in the field of marketing.

Keywords

Data Mining, Marketing, Data Warehouse, Classification, Sequencing, Association, Knowledge.

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Rafi Ahmad Khan ¹, Sharfa Hassan ¹

Affiliations
1 Business School, University of Kashmir, Srinagar, Jammu and Kashmir, IN

Abstract

Case Based Reasoning (CBR) is an Artificial Intelligence (AI) Technique for solving problems by using past experience instances. The centrality of this concept lies in using past solved problems in similar situations to approximate past solutions for such problem situations. This concept has caught the attention of both academicians and practitioners as it has developed as an important technique of AI. CBR has been used with Data Management System (DMS) and Model Management system (MMS) of a Decision Support System (DSS) to provide an integrated framework for smooth and effective managerial decision making. Since decision making is the essence of every manager's job in any area of specialization, therefore, this paper discusses this integration part of Case Based Reasoning and how it assists mangers in effective decision making.

Keywords

Artificial Intelligence, Decision Making, Experience, Problem Solving, Case Based Reasoning (CBR).

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Rafi Ahmad Khan ¹, Sharfa Hassan ¹

Affiliations
1 Business School, University of Kashmir, Srinagar, Jammu and Kashmir, IN

Abstract

Case based reasoning is an extended research field in Artificial Intelligence. It is an Artificial Intelligence technique for problem solving by using past experiences. The concept emerged in US and now it has spread to other continents with Europe having the most active research in Case based reasoning (CBR). Most of the Artificial Intelligence techniques are confined to a general knowledge base of the problem domain and then making generalized inferences to solve a problem. But CBR as an Artificial Intelligence (AI) technique brings the element of actual human behavior to the domain of AI. CBR relies on experiences with the help of which it reasons and solves the problem situation. This approach to AI has really captured the essence of human intelligence which improves with their age. CBR not only keeps the database of past experiences, but with more use of its experiences its reasoning improves. It updates its memory and learns from what it does that makes it different from other AI approaches. Therefore, learning is an important aspect in case based reasoning. In this paper first the working of a typical CBR system is presented followed by some application areas where it will be seen to what extent this concept has been used in actual practice.

Keywords

Artificial Intelligence (AI), Case Based Reasoning (CBR), Problem Solving, Learning, Experience.

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Rafi Ahmad Khan ¹, Sabreen Kanth ¹

Affiliations
1 Business School, University of Kashmir, Srinagar, Jammu and Kashmir, IN

Abstract

Everyday academic, economic, business and social activities lead to generation of huge amount of new data and information. This content of data which is predicted to increase at enormous rate each year has significant value be it societal or economic. The automatic detection of similarity between texts and the determination of relevance of documents relative to a certain query is therefore essential to exploit the potential of this enormous amount of data available. Text-Mining is the technique that is used to automatically discover and extract information/knowledge from the huge volume of semi-structured or unstructured data. Keeping in view the importance of Text-Mining, this paper discusses the concept of Text-Mining and also provides a framework to form the step by step model of Textual Data Mining. It also discusses tools of Text Mining as well as its applications and limitation.

Keywords

Textual Data Mining (TDM), Data Mining (DM), Natural Language Processing (NLP), Information Extraction (IE), Information Retrieval (IR), Data Warehouse (DW), Intermediate Form (IF).

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