Data Mining Applications On Web Usage Analysis & User Profiling

Tez (Yüksek Lisans) -- İstanbul Teknik Üniversitesi, Fen Bilimleri Enstitüsü, 2003Thesis (M.Sc.) -- İstanbul Technical University, Institute of Science and Technology, 2003Tez çalışmasında veri madenciliği teknolojisi, fonksiyonları ve uygulamaları özetlenmiştir. OLAP teknolojilerine ve veri ambarlarına da veri madenciliğinin anahtar kavramları olarak değinilmiştir. Uygulama kısmında müşteri ve alışveriş kalıpları analizi için bir internet parakendecisinin işlemsel verileri kullanılmıştır. Müşteri segmentasyonu ve kullanıcı betimleme gibi konulardaki kurumsal kararları desteklemek amacıyla veri içerisindeki kalıplar çıkarılmaya çalışılmıştır.This thesis gives a summary of data mining technology, its functionalities and applications. OLAP technology and data warehouses are also introduced as the key concepts in data mining. The usage of data mining on the internet and the decisions based on internet usage data are introduced. In the application section a web retailer’s transactional data is used for analyzing customer and shopping patterns.Hidden patterns within the data are tried to be extracted in order to support business decisions such as user profiling and customer segmentation.Yüksek LisansM.Sc

Semantic discovery and reuse of business process patterns

Patterns currently play an important role in modern information systems (IS) development and their use has mainly been restricted to the design and implementation phases of the development lifecycle. Given the increasing significance of business modelling in IS development, patterns have the potential of providing a viable solution for promoting reusability of recurrent generalized models in the very early stages of development. As a statement of research-in-progress this paper focuses on business process patterns and proposes an initial methodological framework for the discovery and reuse of business process patterns within the IS development lifecycle. The framework borrows ideas from the domain engineering literature and proposes the use of semantics to drive both the discovery of patterns as well as their reuse

Modeling and evaluation of knowledge discovery in wholesale and retail industry

x, 168 leaves : ill. ; 29 cm.Includes abstract.Includes bibliographical references (leaves 163-168).This thesis demonstrates an enterprise-wide Knowledge Discovery in Databases (KDD) process CRISP for wholesale and retail industry, which can facilitate business decision-making processes and improve corporate profits. While part of the KDD process described here is well documented, the modeling and evaluations used in the commercial products is not reported in literature. Hence, the focus of this thesis is on the development and evaluation of models used in the knowledge discovery. Description of the underlying models will help the decision makers better understand the quality and limitations of the KDD process. The usefulness of KDD process CRISP is illustrated for two companies, i.e. a multinational retailer and a small chain of specialty grocery stores. The detailed steps highlight business understanding, data exploration, data preparation. data modeling, results evaluation, and interpretation. The methodologies applied in this thesis include prediction, clustering and association to discover knowledge about products/suppliers, consumers, and business units

KEER2022

Avanttítol: KEER2022. DiversitiesDescripció del recurs: 25 juliol 202

New Fundamental Technologies in Data Mining

The progress of data mining technology and large public popularity establish a need for a comprehensive text on the subject. The series of books entitled by "Data Mining" address the need by presenting in-depth description of novel mining algorithms and many useful applications. In addition to understanding each section deeply, the two books present useful hints and strategies to solving problems in the following chapters. The contributing authors have highlighted many future research directions that will foster multi-disciplinary collaborations and hence will lead to significant development in the field of data mining

4th. International Conference on Advanced Research Methods and Analytics (CARMA 2022)

Research methods in economics and social sciences are evolving with the increasing availability of Internet and Big Data sources of information. As these sources, methods, and applications become more interdisciplinary, the 4th International Conference on Advanced Research Methods and Analytics (CARMA) is a forum for researchers and practitioners to exchange ideas and advances on how emerging research methods and sources are applied to different fields of social sciences as well as to discuss current and future challenges. Due to the covid pandemic, CARMA 2022 is planned as a virtual and face-to-face conference, simultaneouslyDoménech I De Soria, J.; Vicente Cuervo, MR. (2022). 4th. International Conference on Advanced Research Methods and Analytics (CARMA 2022). Editorial Universitat Politècnica de València. https://doi.org/10.4995/CARMA2022.2022.1595

Data mining industry : emerging trends and new opportunities

Thesis (M.Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, June 2000."May 2000."Includes bibliographical references (leaves 170-179).by Walter Alberto Aldana.M.Eng

Brain Computer Interfaces and Emotional Involvement: Theory, Research, and Applications

This reprint is dedicated to the study of brain activity related to emotional and attentional involvement as measured by Brain–computer interface (BCI) systems designed for different purposes. A BCI system can translate brain signals (e.g., electric or hemodynamic brain activity indicators) into a command to execute an action in the BCI application (e.g., a wheelchair, the cursor on the screen, a spelling device or a game). These tools have the advantage of having real-time access to the ongoing brain activity of the individual, which can provide insight into the user’s emotional and attentional states by training a classification algorithm to recognize mental states. The success of BCI systems in contemporary neuroscientific research relies on the fact that they allow one to “think outside the lab”. The integration of technological solutions, artificial intelligence and cognitive science allowed and will allow researchers to envision more and more applications for the future. The clinical and everyday uses are described with the aim to invite readers to open their minds to imagine potential further developments