A SURVEY ON EDUCATIONAL DATA MINING AND RESEARCH TRENDS

ABSTRAC

Improving customer generation by analysing website visitor behaviour

This dissertation describes the creation of a new integrated Information Technology (IT) system that assisted in the collection of data about the behaviour of website visitors as well as sales and marketing data for those visitors who turned into customers. A key contribution to knowledge was the creation of a method to predict the outcome of visits to a website from visitors’ browsing behaviour. A new Online Tracking Module (OTM) was created that monitored visitors’ behaviour while they browsed websites. When a visitor converted into a customer, then customer and marketing data as well as sales activity was saved in a new Customer Relationship Management (CRM) system that was implemented in this research. The research focused on service websites. The goal of these websites was to promote products and services online and turn enquiries into offline sales. The challenge faced by these websites was to convince as many visitors as possible to enquire. Most websites relied on Search Engine Optimisation (SEO) and Pay Per Click (PPC) advertising for traffic generation. This research used PPC advertising to generate traffic. An important aspect of PPC advertising was landing page optimisation. The aim of landing page optimisation was to increase the number of visitors to a website who completed a specific action on the website. In the case of the websites investigated in this research the action consisted of completing and sending an enquiry form from the websites. The research looked for meaningful commonalities in the data collected by MS CRM and the OTM and combined this with feedback from the collaborating company’s sales team to create two personas for website visitors who had enquired. Techniques for improving landing pages were identified and these led to changes to landing pages. Some of these changes were targeted at a particular visitor persona. The effect of changes made to a landing page was measured by comparing its conversion rate and bounce rate before and after the changes. Behavioural data collected by the OTM was then analysed using a data mining engine to find models that could predict whether a user would convert based on their browsing behaviour. Models were found that could predict the outcome of a visit to a service website.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Um método de tradução de fontes de informação em um formato padrão que viabilize a extração de conhecimento por meio de link analysis e teoria dos grafos

Dissertação (mestrado) - Universidade Federal de Santa Catarina, Centro Tecnológico. Programa de Pós-Graduação em Engenharia de Produção.O conhecimento tem se configurado como um recurso estratégico nas organizações. Para elas, gerar, codificar, gerir e disseminar o conhecimento organizacional tornaram-se tarefas essenciais. Logo, é necessário o desenvolvimento de novas técnicas, metodologias e formas de extração de conhecimento a partir de fontes de informação que descrevem um domínio de aplicação. Nesse contexto, o objetivo do presente trabalho é propor um método que permita traduzir fontes de informação em um formato padrão de representação de relacionamentos entre elementos do domínio do problema, de forma a viabilizar a extração de conhecimento por meio da aplicação de Link Analysis e Teoria dos Grafos. Além disso, são apresentadas duas aplicações desse modelo na Plataforma Lattes de CT&I

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

The role of textual data in finance: methodological issues and empirical evidence

This thesis investigates the role of textual data in the financial field. Textual data fall into the more extensive category of alternative data. These types of data, such as reviews, blog post, tweet, are constantly growing, and this reinforces the importance in several domains. The thesis explores different applications of textual data in finance to highlight how it is possible to use this type of data and how this implementation can add value to financial analysis. The first application concerns the use of a lexicon-based approach in the credit scoring model. The second application proposes a causality detection between financial and sentiment data using an information-theoretic measure, the transfer entropy. The last application concerns the use of sentiment analysis in a network model, called BGVAR, to analyze the financial impact of the Covid-19 Pandemic. Overall, this thesis shows that combining textual data with traditional financial data can lead to a more insightful knowledge and, therefore, to a more in-depth analysis, allowing for a broader understanding of economic events and financial relationships among economic entities of any kind

Recent Developments in Cancer Systems Biology

This ebook includes original research articles and reviews to update readers on the state of the art systems approach to not only discover novel diagnostic and prognostic biomarkers for several cancer types, but also evaluate methodologies to map out important genomic signatures. In addition, therapeutic targets and drug repurposing have been emphasized for a variety of cancer types. In particular, new and established researchers who desire to learn about cancer systems biology and why it is possibly the leading front to a personalized medicine approach will enjoy reading this book