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Articles 1 - 5 of 5
Full-Text Articles in Computer Sciences
Alpha Insurance: A Predictive Analytics Case To Analyze Automobile Insurance Fraud Using Sas Enterprise Miner (Tm), Richard Mccarthy, Wendy Ceccucci, Mary Mccarthy, Leila Halawi
Alpha Insurance: A Predictive Analytics Case To Analyze Automobile Insurance Fraud Using Sas Enterprise Miner (Tm), Richard Mccarthy, Wendy Ceccucci, Mary Mccarthy, Leila Halawi
Publications
Automobile Insurance fraud costs the insurance industry billions of dollars annually. This case study addresses claim fraud based on data extracted from Alpha Insurance’s automobile claim database. Students are provided the business problem and data sets. Initially, the students are required to develop their hypotheses and analyze the data. This includes identification of any missing or inaccurate data values and outliers as well as evaluation of the 22 variables. Next students will develop and optimize their predictive models using five techniques: regression, decision tree, neural network, gradient boosting, and ensemble. Then students will determine which model is the best fit …
Applications Of Supervised Machine Learning In Autism Spectrum Disorder Research: A Review, Kayleigh K. Hyde, Marlena N. Novack, Nicholas Lahaye, Chelsea Parlett-Pelleriti, Raymond Anden, Dennis R. Dixon, Erik Linstead
Applications Of Supervised Machine Learning In Autism Spectrum Disorder Research: A Review, Kayleigh K. Hyde, Marlena N. Novack, Nicholas Lahaye, Chelsea Parlett-Pelleriti, Raymond Anden, Dennis R. Dixon, Erik Linstead
Engineering Faculty Articles and Research
Autism spectrum disorder (ASD) research has yet to leverage "big data" on the same scale as other fields; however, advancements in easy, affordable data collection and analysis may soon make this a reality. Indeed, there has been a notable increase in research literature evaluating the effectiveness of machine learning for diagnosing ASD, exploring its genetic underpinnings, and designing effective interventions. This paper provides a comprehensive review of 45 papers utilizing supervised machine learning in ASD, including algorithms for classification and text analysis. The goal of the paper is to identify and describe supervised machine learning trends in ASD literature as …
Wordnet-Based Criminal Networks Mining For Cybercrime Investigation, Farkhund Iqbal, Benjamin C.M. Fung, Mourad Debbabi, Rabia Batool, Andrew Marrington
Wordnet-Based Criminal Networks Mining For Cybercrime Investigation, Farkhund Iqbal, Benjamin C.M. Fung, Mourad Debbabi, Rabia Batool, Andrew Marrington
All Works
© 2019 IEEE. Cybercriminals exploit the opportunities provided by the information revolution and social media to communicate and conduct underground illicit activities, such as online fraudulence, cyber predation, cyberbullying, hacking, blackmailing, and drug smuggling. To combat the increasing number of criminal activities, structure and content analysis of criminal communities can provide insight and facilitate cybercrime forensics. In this paper, we propose a framework to analyze chat logs for crime investigation using data mining and natural language processing techniques. The proposed framework extracts the social network from chat logs and summarizes conversation into topics. The crime investigator can use information visualizer …
Exploratory Factor Analysis Of Graphical Features For Link Prediction In Social Networks, Lale Madahali, Lotfi Najjar, Margeret Hall
Exploratory Factor Analysis Of Graphical Features For Link Prediction In Social Networks, Lale Madahali, Lotfi Najjar, Margeret Hall
Interdisciplinary Informatics Faculty Proceedings & Presentations
Social Networks attract much attention due to their ability to replicate social interactions at scale. Link prediction, or the assessment of which unconnected nodes are likely to connect in the future, is an interesting but non-trivial research area. Three approaches exist to deal with the link prediction problem: feature-based models, Bayesian probabilistic models, probabilistic relational models. In feature-based methods, graphical features are extracted and used for classification. Usually, these features are subdivided into three feature groups based on their formula. Some formulas are extracted based on neighborhood graph traverse. Accordingly, there exists three groups of features, neighborhood features, path-based features, …
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 …