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Full-Text Articles in Computer Sciences
Brexit: A Granger Causality Of Twitter Political Polarisation On The Ftse 100 Index And The Pound, James Usher, Lucia Morales, Pierpaolo Dondio
Brexit: A Granger Causality Of Twitter Political Polarisation On The Ftse 100 Index And The Pound, James Usher, Lucia Morales, Pierpaolo Dondio
Conference papers
BREXIT is the single biggest geopolitical event in British history since WWII. Whilst the political fallout has become a tragicomedy, the political ramifications has had a profound impact on the Pound and the FTSE 100 index. This paper examines Twitter political discourse surrounding the BREXIT withdrawal agreement. In particular we focus on the discussions around four different exit strategies known as “Norway”, “Article 50”, the“Backstop” and “No Deal” and their effect on the pound and FTSE 100 index from the period of rumblings of the cancellation of the Meaning Vote on December 10th 2018 inclusive of second defeat on the …
Classification Using Association Rules, Colin Kane
Classification Using Association Rules, Colin Kane
Dissertations
This research investigates the use of an unsupervised learning technique, association rules, to make class predictions. The use of association rules to make class predictions is a growing area of focus within data mining research. The research to date has focused predominately on balanced datasets or synthetized imbalanced datasets. There have been concerns raised that the algorithms using association rules to make classifications do not perform well on imbalanced datasets. This research comprehensively evaluates the accuracy of a number of association rule classifiers in predicting home loan sales in an Irish retail banking context. The experiments designed test three associative …
Clicking Into Mortgage Arrears: A Study Into Arrears Prediction With Clickstream Data, Gavin O'Brien
Clicking Into Mortgage Arrears: A Study Into Arrears Prediction With Clickstream Data, Gavin O'Brien
Dissertations
This research project investigates the predictive capability of clickstream data when used for the purpose of mortgage arrears prediction. With an ever growing number of people switching to digital channels to handle their daily banking requirements, there is a wealth of ever increasing online usage data, otherwise known as clickstream data. If leveraged correctly, this clickstream data can be a powerful data source for organisations as it provides detailed information about how their customers are interacting with their digital channels. Much of the current literature associated with clickstream data relates to organisations employing it within their customer relationship management mechanisms …
Data Mining By Grid Computing In The Search For Extrasolar Planets, Oisin Creaner [Thesis]
Data Mining By Grid Computing In The Search For Extrasolar Planets, Oisin Creaner [Thesis]
Doctoral
A system is presented here to provide improved precision in ensemble differential photometry. This is achieved by using the power of grid computing to analyse astronomical catalogues. This produces new catalogues of optimised pointings for each star, which maximise the number and quality of reference stars available. Astronomical phenomena such as exoplanet transits and small-scale structure within quasars may be observed by means of millimagnitude photometric variability on the timescale of minutes to hours. Because of atmospheric distortion, ground-based observations of these phenomena require the use of differential photometry whereby the target is compared with one or more reference stars. …
Sentiment Classification Of Reviews Using Sentiwordnet, Bruno Ohana, Brendan Tierney
Sentiment Classification Of Reviews Using Sentiwordnet, Bruno Ohana, Brendan Tierney
Conference papers
Sentiment classification concerns the use of automatic methods for predicting the orientation of subjective content on text documents, with applications on a number of areas including recommender and advertising systems, customer intelligence and information retrieval. SentiWordNet is an opinion lexicon derived from the WordNet database where each term is associated with numerical scores indicating positive and negative sentiment information. This research presents the results of applying the SentiWordNet lexical resource to the problem of automatic sentiment classification of film reviews. Our approach comprises counting positive and negative term scores to determine sentiment orientation, and an improvement is presented by building …
An Enhanced Data Mining Life Cycle, Markus Hofmann, Brendan Tierney
An Enhanced Data Mining Life Cycle, Markus Hofmann, Brendan Tierney
Conference papers
Data mining projects are complex and can have a high failure rate. In order to improve project management and success rates of such projects a life cycle is vital to the overall success of the project. This paper reports on a research project that was concerned with the life cycle development for data mining projects, its team members and their role. The paper provides a detailed view of the design and development of the data mining life cycle called DMLC. The life cycle aims to support all members of data mining project teams as well as IT managers and academic …