as google analytics becomes increasingly popular, more detailed records of users’ behaviors can be captured and analyzed to better understand the performance of websites. however, current google analytics related research usually draws conclusions from rough estimation based on the observation of the dashboard or other basic statistical processing of the data. this study aims to provide a more ...

data about the prevalence of communicable and non-communicable diseases, as one of the most important categories of epidemiological data, is used for interpreting health status of communities. this study aims to calculate the prevalence of outpatient diseases through the characterization of outpatient prescriptions. the data used in this study is collected from 1412 prescriptions for various ty...

background : chronic kidney disease (ckd) is a complicated kidney problem causing permanent renal failure in progressive stages. the final stage of ckd is called esrd in which most accepted management is hemodialysis (hd). arterio-venus fistula (avf) is the most practical way of making proper access to the blood circulatory system however, maturation of the avf is a challenge, since there are n...

business all around the world uses different approaches to know their customers, segment them and formulate suitable strategies for them. one of these approaches is calculating the value of each customer for the company. in this paper by calculating customer lifetime value (clv) for individual customers of an online toy store named alakdolak, three customer segments are extracted. the level of ...

Space and time are implicit in every activity of life. Every real-world object has its past, present, future and hence is intrinsically tied up with location and time. Storing spatio-temporal attributes in the databases along with the thematic attributes enriches the data and the inherent knowledge stored in the database. Spatio-temporal databases provide description of real-world phenomenon in...

To address the data and technical challenges facing ISI, we present a research framework with a primary focus on KDD (Knowledge Discovery from Databases) technologies. The framework is discussed in the context of crime types and security implications. Selected data mining techniques, including information sharing and collaboration, association mining, classification and clustering, text mining,...

decision support systems (dsss) are prevalent information systems for decision making in many competitive business environments. in a dss, decision making process is intimately related to some factors which determine the quality of information systems and their related products. traditional approaches to data analysis usually cannot be implemented in sophisticated companies, where managers need...

decision-tree algorithms provide one of the most popular methodologies for symbolic knowledge acquisition. the resulting knowledge, a symbolic decision tree along with a simple inference mechanism, has been praised for comprehensibility. the most comprehensible decision trees have been designed for perfect symbolic data. classical crisp decision trees (dt) are widely applied to classification t...

decision support systems (dsss) are prevalent information systems for decision making in many competitive business environments. in a dss, decision making process is intimately related to some factors which determine the quality of information systems and their related products. traditional approaches to data analysis usually cannot be implemented in sophisticated companies, where managers nee...

The issue addressed in this paper concerns the discovery of frequent multi-dimensional patterns from relational sequences. The great variety of applications of sequential pattern mining, such as user profiling, medicine, local weather forecast and bioinformatics, makes this problem one of the central topics in data mining. Nevertheless, sequential information may concern data on multiple dimens...