With the rise of various streaming services like Netflix and Amazon Prime, and the rise of movie collections offered by a single provider, the need for determining user-specific movie ratings increases. It is highly crucial for a company to know, and recommend the type of movies liked by users to increase customer retention and improve user experience. In this paper, we are going to use data mi...

Clickstream analysis can reveal usage patterns on company’s web sites giving highly improved understanding of customer behaviour. This can be used to improve customer satisfaction with the website and the company in general, yielding a great business advantage. Such information has to be extracted from very large collections of clickstreams in web sites. This is challenging data mining, both in...

Opinions are always very important for human beings. Whenever a decision has been carried out, people always consult with the friends and relatives. But from the last few years , the impact of the web has surprisingly increased, for peoples web documents act as a new source of opinion. Nowadays each company allows its customers to write their opinions related to their products, so large numbers...

Using data mining techniques, this study attempts to explore how a proper layout zoning following class-based storage enhances order picking efficiency over randomized storage. Association web statistics and association rule mining examines the relative intensity levels among various product categories. These findings serve as the layout for zoning of the storage area of α company, a pharmaceut...

Supplier intelligence represents an important type of competitive intelligence essential to organizational strategic planning and analysis, because the moves that the suppliers of a firm make will affect the business network’s health, which in turn will impact the performance of the firm. Central to supplier intelligence is to identify who the suppliers of a focal firm and its competitors are. ...

Correctness, transparency and effectiveness are the principal attributes of knowledge derived from databases using data mining. In the current data mining research there is a focus on efficiency improvement of algorithms for knowledge discovery. However, improving the algorithms is often not sufficient. The limitations of data mining can only be dissolved by the integration of knowledge of expe...

Living through the Information Revolution is becoming a diicult task-humans were not designed to process massive quantities of information. The computer rst found it's use in speeding our number crunching, performing a large number of calculations blindingly fast. We are now beginning to turn to computers to solve another human inadequacy, mining through our masses of information to nd items of...

Managed Security Services (MSS) have become an essential asset for companies to have in order to protect their infrastructure from hacking attempts such as unauthorized behaviour, denial of service (DoS), malware propagation, and anomalies. A proliferation of attacks has determined the need for installing more network probes and collecting more security-related events in order to assure the bes...

Processes are not always executed as expected. Deviations assure the necessary flexibility within a company, but also increase possible internal control weaknesses. Since the number of cases following such a deviation can grow very large, it becomes difficult to analyze them case-by-case. This paper proposes a semi-automatic process deviation analysis method which combines process mining with a...

While the maturity of process mining algorithms increases and more process mining tools enter the market, process mining projects still face the problem of different levels of abstraction when comparing events with modeled business activities. Current approaches for event log abstraction try to abstract from the events in an automated way that does not capture the required domain knowledge to f...