Abstract In this paper, we investigated the utility of data mining to classify individuals into predefined categories of a target variable, based on their social and political attitude. Data collected for a social psychology study conducted in Greece in 1994 were used for this purpose. We...

Purpose – The aim of this paper is to develop a new user‐friendly in‐house tracking methodology for academics to analyse the effectiveness of visits (return visit behaviour and length of sessions) depending on their traffic source: direct visits, referring site entries and search engine...

Purpose – The study seeks to apply Web co‐word analysis to the Chinese business environment to test the feasibility of the method there. Design/methodology/approach – The authors selected a group of companies in two Chinese industries, collected co‐word data for the companies, analyzed...

Purpose – The purpose of this paper is to explore the role of business intelligence (BI) in a consulting company. The authors propose to analyze quality through data analysis and efficiency under different business contexts. The best processes and tools in data mining are also explored....

Purpose – Process mining is a research area used to discover, monitor and improve real business processes by extracting knowledge from event logs available in process-aware information systems. The purpose of this paper is to evaluate the application of artificial neural networks (ANNs) and...

Purpose Class imbalance learning, which exists in many domain problem datasets, is an important research topic in data mining and machine learning. One-class classification techniques, which aim to identify anomalies as the minority class from the normal data as the majority class, are one...

Purpose This study identifies whether the Internet search index can be used as effective enough data to identify agricultural and livestock product demand and compare the accuracy of the prediction of major agricultural and livestock products purchases between these prediction models using...

Purpose Frequent itemset mining (FIM) is a basic topic in data mining. Most FIM methods build itemset database containing all possible itemsets, and use predefined thresholds to determine whether an itemset is frequent. However, the algorithm has some deficiencies. It is more fit for discrete...

Purpose This work provides a generic review of the existing data mining ontologies (DMOs) and also provides a base platform for ontology developers and researchers for gauging the ontologies for satisfactory coverage and usage. Design/methodology/approach The study uses a systematic literature...

Purpose The spatial and non-spatial attributes are the two important characteristics of a spatial point, which belong to the two different attribute domains in many Geographic Information Systems applications. The dual clustering algorithms take into account both spatial and non-spatial...