Intelligent customer relationship management (ICRM) by EFLOW portal

Customer relationship management (CRM) has become a strategic initiative aimed at getting, growing, and retaining the right customers. A great amount of numeric data and even more soft information are available about customers. The strategy of building and maintaining customer relations can be described with 'if… then' rules acquired from experts. Doctus Knowledge-Based System provides a new and simplified approach in the field of knowledge management. It is able to cope with tacit and implicit rules at the same time, so decision makers can clearly see the satisfactory solution (then and there). It reasons both deductive and inductive, so it enables the user to check on the model graph why is the chosen solution in the given situation most appropriate. It is upgradeable with in telligent portal, which presents the personalized (body-tailored) information for decision makers. When we need some hard data from a database or a data warehouse, we have automatic connection between case input interface and the database. Doctus recognizes the relations between the data, it selects them and provides only the needed rules to the decision maker. Intelligent portal puts our experience on the web, so our knowledge base is constantly improving with new 'if… then' rules. We support decision mak ing with two interfaces. On the Developer Interface the attributes, the values and the 'if… then' rules can be modified. The intelligent portal is used as a managerial decision support tool. This interface can be used without seeing the knowledge base, we only see the personalized soft information. ICRM (intelligent Customer Relationship Management) helps customer to get the requested information quickly. It is also capable of customizing the questionnaires, so the customer doesn't have to answer irrelevant questions and the decision maker doesn't have to read endless reports

Datamining for Web-Enabled Electronic Business Applications

Web-Enabled Electronic Business is generating massive amount of data on customer purchases, browsing patterns, usage times and preferences at an increasing rate. Data mining techniques can be applied to all the data being collected for obtaining useful information. This chapter attempts to present issues associated with data mining for web-enabled electronic-business

On-line analytical processing

On-line analytical processing (OLAP) describes an approach to decision support, which aims to extract knowledge from a data warehouse, or more specifically, from data marts. Its main idea is providing navigation through data to non-expert users, so that they are able to interactively generate ad hoc queries without the intervention of IT professionals. This name was introduced in contrast to on-line transactional processing (OLTP), so that it reflected the different requirements and characteristics between these classes of uses. The concept falls in the area of business intelligence.Peer ReviewedPostprint (author's final draft