In Today’s quality- based competitive world, known as knowledge age, customer attraction is of ultimate importance. In respect to the slogan “customer is always right”, customer relation management is the core of an organizational strategy playing an important role in four aspects of customer identification, customer attraction, customer retaining, and customer satisfaction. Commercial organiza...

A major concern for modern enterprises is to promote customer value, loyalty and contribution through services such as can help establish a long-term, honest relationship with customers. For purposes of better customer relationship management, data mining technology is commonly used to analyze large quantities of data about customer bargains, purchase preferences, customer churn, etc. This pape...

This paper summarizes experiences and results of productively using knowledge discovery and data mining technology in a large retail bank. We present data mining as part of a greater e ort to develop and deploy an integrated IT-infrastructure for loyalty based customer management, combining data warehousing, and campaign management together with data mining technology. We have completed a rst c...

Customer churn prediction is one of the most important elements of any Customer Relationship Management (CRM) strategy. In this study, a number of strategies are investigated to increase the lift of ensemble classification models. In order to increase lift performance, two elements of a number of well-known ensemble strategies are altered: (i) the potential of using probability estimation trees...

Enterprises are increasingly using social media forums to engage with their customer onlinea phenomenon known as Social Customer Relation Management (Social CRM). In this context, it is important for an enterprise to identify “influential authors” and engage with them on a priority basis. We present a study towards finding influential authors on Twitter forums where an implicit network based on...

In this paper, we mainly explore the effectiveness of two kernelbased methods, the convolution tree kernel and the shortest path dependency kernel, for Chinese relation extraction based on ACE 2007 corpus. For the convolution kernel, the performances of different parse tree spans involved in it for relation extraction are studied. Then, experiments with composite kernels, which are a combinatio...

Keyword search is a friendly mechanism for the end user to identify interesting nodes in XML databases, and the SLCA (smallest lowest common ancestor)-based keyword search is a popular concept for locating the desirable subtrees corresponding to the given query keywords. However, it does not evaluate the importance of each node under those subtrees. Liu and Chen proposed a new concept contribut...

The task of relation extraction is to recognize and extract relations between entities or concepts in texts. Dependency parse trees have become a popular source for discovering extraction patterns, which encode the grammatical relations among the phrases that jointly express relation instances. State-of-the-art weakly supervised approaches to relation extraction typically extract thousands of u...

Consider any fixed graph whose edges have been randomly and independently oriented, and write {S i} to indicate that there is an oriented path going from a vertex s ∈ S to vertex i. Narayanan (2016) proved that for any set S and any two vertices i and j, {S i} and {S j} are positively correlated. His proof relies on the Ahlswede-Daykin inequality, a rather advanced tool of probabilistic combina...

Customer churn means the loss of existing customers to a competitor. Accurately predicting customer behavior may help firms to minimize this loss by proactively building a lasting relationship with their customers. In this paper, the application of the factor analysis and the Variable Consistency Dominance-based Rough Set Approach (VC-DRSA) in the customer relationship management (CRM) of the a...