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Full-Text Articles in Computer Sciences
Prevalence, Contents And Automatic Detection Of Kl-Satd, Leevi Rantala, Mika Mantyla, David Lo
Prevalence, Contents And Automatic Detection Of Kl-Satd, Leevi Rantala, Mika Mantyla, David Lo
Research Collection School Of Computing and Information Systems
When developers use different keywords such as TODO and FIXME in source code comments to describe self-admitted technical debt (SATD), we refer it as Keyword-Labeled SATD (KL-SATD). We study KL-SATD from 33 software repositories with 13,588 KL-SATD comments. We find that the median percentage of KL-SATD comments among all comments is only 1,52%. We find that KL-SATD comment contents include words expressing code changes and uncertainty, such as remove, fix, maybe and probably. This makes them different compared to other comments. KL-SATD comment contents are similar to manually labeled SATD comments of prior work. Our machine learning classifier using logistic …
Joint Lattice Of Reconstructability Analysis And Bayesian Network General Graphs, Marcus Harris, Martin Zwick
Joint Lattice Of Reconstructability Analysis And Bayesian Network General Graphs, Marcus Harris, Martin Zwick
Systems Science Faculty Publications and Presentations
This paper integrates the structures considered in Reconstructability Analysis (RA) and those considered in Bayesian Networks (BN) into a joint lattice of probabilistic graphical models. This integration and associated lattice visualizations are done in this paper for four variables, but the approach can easily be expanded to more variables. The work builds on the RA work of Klir (1985), Krippendorff (1986), and Zwick (2001), and the BN work of Pearl (1985, 1987, 1988, 2000), Verma (1990), Heckerman (1994), Chickering (1995), Andersson (1997), and others. The RA four variable lattice and the BN four variable lattice partially overlap: there are ten …
Reconstructability Analysis & Its Occam Implementation, Martin Zwick
Reconstructability Analysis & Its Occam Implementation, Martin Zwick
Systems Science Faculty Publications and Presentations
This talk will describe Reconstructability Analysis (RA), a probabilistic graphical modeling methodology deriving from the 1960s work of Ross Ashby and developed in the systems community in the 1980s and afterwards. RA, based on information theory and graph theory, resembles and partially overlaps Bayesian networks (BN) and log-linear techniques, but also has some unique capabilities. (A paper explaining the relationship between RA and BN will be given in this special session.) RA is designed for exploratory modeling although it can also be used for confirmatory hypothesis testing. In RA modeling, one either predicts some DV from a set of IVs …
Probabilistic Value Selection For Space Efficient Model, Gunarto Sindoro Njoo, Baihua Zheng, Kuo-Wei Hsu, Wen-Chih Peng
Probabilistic Value Selection For Space Efficient Model, Gunarto Sindoro Njoo, Baihua Zheng, Kuo-Wei Hsu, Wen-Chih Peng
Research Collection School Of Computing and Information Systems
An alternative to current mainstream preprocessing methods is proposed: Value Selection (VS). Unlike the existing methods such as feature selection that removes features and instance selection that eliminates instances, value selection eliminates the values (with respect to each feature) in the dataset with two purposes: reducing the model size and preserving its accuracy. Two probabilistic methods based on information theory's metric are proposed: PVS and P + VS. Extensive experiments on the benchmark datasets with various sizes are elaborated. Those results are compared with the existing preprocessing methods such as feature selection, feature transformation, and instance selection methods. Experiment results …
Developing Big Data Projects In Open University Engineering Courses: Lessons Learned, Juan A. Lara, Aurea Anguera De Sojo, Shadi Aljawarneh, Robert P. Schumaker, Bassam Al-Shargabi
Developing Big Data Projects In Open University Engineering Courses: Lessons Learned, Juan A. Lara, Aurea Anguera De Sojo, Shadi Aljawarneh, Robert P. Schumaker, Bassam Al-Shargabi
Computer Science Faculty Publications and Presentations
Big Data courses in which students are asked to carry out Big Data projects are becoming more frequent as a part of University Engineering curriculum. In these courses, instructors and students must face a series of special characteristics, difficulties and challenges that it is important to know about beforehand, so the lecturer can better plan the subject and manage the teaching methods in order to prevent students' academic dropout and low performance. The goal of this research is to approach this problem by sharing the lessons learned in the process of teaching e-learning courses where students are required to develop …
A Framework For Online Social Network Volatile Data Analysis: A Case For The Fast Fashion Industry, Anoud Bani-Hani, Feras Al-Obeidat, Elhadj Benkhelifa, Oluwasegun Adedugbe
A Framework For Online Social Network Volatile Data Analysis: A Case For The Fast Fashion Industry, Anoud Bani-Hani, Feras Al-Obeidat, Elhadj Benkhelifa, Oluwasegun Adedugbe
All Works
Consumer satisfaction is an important part for any business as it has been shown to be a major factor for consumer loyalty. Identifying satisfaction in products is also important as it allows businesses alter production plans based on the level of consumer satisfaction for a product. With consumer satisfaction data being very volatile for some products due to a short requirement period for such products, current consumer satisfaction must be identified within a shorter period before the data becomes obsolete. The fast fashion industry, which is part of the fashion industry, is adopted as a case study in this research. …