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Articles 601 - 625 of 625
Full-Text Articles in Databases and Information Systems
High-Dimensional Software Engineering Data And Feature Selection, Huanjing Wang, Taghi M. Khoshgoftaar, Kehan Gao
High-Dimensional Software Engineering Data And Feature Selection, Huanjing Wang, Taghi M. Khoshgoftaar, Kehan Gao
Computer Science Faculty Publications
Software metrics collected during project development play a critical role in software quality assurance. A software practitioner is very keen on learning which software metrics to focus on for software quality prediction. While a concise set of software metrics is often desired, a typical project collects a very large number of metrics. Minimal attention has been devoted to finding the minimum set of software metrics that have the same predictive capability as a larger set of metrics – we strive to answer that question in this paper. We present a comprehensive comparison between seven commonly-used filter-based feature ranking techniques (FRT) …
An Empirical Investigation Of Filter Attribute Selection Techniques For Software Quality Classification, Kehan Gao, Taghi M. Khoshgoftaar, Huanjing Wang
An Empirical Investigation Of Filter Attribute Selection Techniques For Software Quality Classification, Kehan Gao, Taghi M. Khoshgoftaar, Huanjing Wang
Computer Science Faculty Publications
Attribute selection is an important activity in data preprocessing for software quality modeling and other data mining problems. The software quality models have been used to improve the fault detection process. Finding faulty components in a software system during early stages of software development process can lead to a more reliable final product and can reduce development and maintenance costs. It has been shown in some studies that prediction accuracy of the models improves when irrelevant and redundant features are removed from the original data set. In this study, we investigated four filter attribute selection techniques, Automatic Hybrid Search (AHS), …
Setting Discrete Bid Levels Adaptively In Repeated Auctions, Jilian Zhang, Hoong Chuin Lau, Jialie Shen
Setting Discrete Bid Levels Adaptively In Repeated Auctions, Jilian Zhang, Hoong Chuin Lau, Jialie Shen
Research Collection School Of Computing and Information Systems
The success of an auction design often hinges on its ability to set parameters such as reserve price and bid levels that will maximize an objective function such as the auctioneer revenue. Works on designing adaptive auction mechanisms have emerged recently, and the challenge is in learning different auction parameters by observing the bidding in previous auctions. In this paper, we propose a non-parametric method for determining discrete bid levels dynamically so as to maximize the auctioneer revenue. First, we propose a non-parametric kernel method for estimating the probabilities of closing price with past auction data. Then a greedy strategy …
A Self-Organizing Neural Network Architecture For Intentional Planning Agents, Budhitama Subagdja, Ah-Hwee Tan
A Self-Organizing Neural Network Architecture For Intentional Planning Agents, Budhitama Subagdja, Ah-Hwee Tan
Research Collection School Of Computing and Information Systems
This paper presents a model of neural network embodiment of intentions and planning mechanisms for autonomous agents. The model bridges the dichotomy of symbolic and non-symbolic representation in developing agents. Some novel techniques are introduced that enables the neural network to process and manipulate sequential and hierarchical structures of information. It is suggested that by incorporating intentional agent model which relies on explicit symbolic description with self-organizing neural networks that are good at learning and recognizing patterns, the best from both sides can be exploited. This paper demonstrates that plans can be represented as weighted connections and reasoning processes can …
Recursive Pattern Based Hybrid Supervised Training, Kiruthika Ramanathan, Sheng Uei Guan
Recursive Pattern Based Hybrid Supervised Training, Kiruthika Ramanathan, Sheng Uei Guan
Research Collection School Of Computing and Information Systems
We propose, theorize and implement the Recursive Pattern-based Hybrid Supervised (RPHS) learning algorithm. The algorithm makes use of the concept of pseudo global optimal solutions to evolve a set of neural networks, each of which can solve correctly a subset of patterns. The pattern-based algorithm uses the topology of training and validation data patterns to find a set of pseudo-optima, each learning a subset of patterns. It is therefore well adapted to the pattern set provided. We begin by showing that finding a set of local optimal solutions is theoretically equivalent, and more efficient, to finding a single global optimum …
Enhancing Recursive Supervised Learning Using Clustering And Combinatorial Optimization (Rsl-Cc), Kiruthika Ramanathan, Sheng Uei Guan
Enhancing Recursive Supervised Learning Using Clustering And Combinatorial Optimization (Rsl-Cc), Kiruthika Ramanathan, Sheng Uei Guan
Research Collection School Of Computing and Information Systems
The use of a team of weak learners to learn a dataset has been shown better than the use of one single strong learner. In fact, the idea is so successful that boosting, an algorithm combining several weak learners for supervised learning, has been considered to be one of the best off-the-shelf classifiers. However, some problems still remain, including determining the optimal number of weak learners and the overfitting of data. In an earlier work, we developed the RPHP algorithm which solves both these problems by using a combination of genetic algorithm, weak learner and pattern distributor. In this paper, …
Medical Language Processing For Patient Diagnosis Using Text Classification And Negation Labelling, Brian Mac Namee, John D. Kelleher, Sarah Jane Delany
Medical Language Processing For Patient Diagnosis Using Text Classification And Negation Labelling, Brian Mac Namee, John D. Kelleher, Sarah Jane Delany
Conference papers
This paper describes the approach of the DIT AIGroup to the i2b2 Obesity Challenge to build a system to diagnose obesity and related co-morbidities from narrative, unstructured patient records. Based on experimental results a system was developed which used knowledge-light text classification using decision trees, and negation labelling.
A Classifier To Evaluate Language Specificity In Medical Documents, Trudi Miller '08, Gondy A. Leroy, Samir Chatterjee, Jie Fan, Brian Thoms '09
A Classifier To Evaluate Language Specificity In Medical Documents, Trudi Miller '08, Gondy A. Leroy, Samir Chatterjee, Jie Fan, Brian Thoms '09
CGU Faculty Publications and Research
Consumer health information written by health care professionals is often inaccessible to the consumers it is written for. Traditional readability formulas examine syntactic features like sentence length and number of syllables, ignoring the target audience's grasp of the words themselves. The use of specialized vocabulary disrupts the understanding of patients with low reading skills, causing a decrease in comprehension. A naive Bayes classifier for three levels of increasing medical terminology specificity (consumer/patient, novice health learner, medical professional) was created with a lexicon generated from a representative medical corpus. Ninety-six percent accuracy in classification was attained. The classifier was then applied …
Integrating Semantic Templates With Decision Tree For Image Semantic Learning, Ying Liu, Dengsheng Zhang, Guojun Lu, Ah-Hwee Tan
Integrating Semantic Templates With Decision Tree For Image Semantic Learning, Ying Liu, Dengsheng Zhang, Guojun Lu, Ah-Hwee Tan
Research Collection School Of Computing and Information Systems
Decision tree (DT) has great potential in image semantic learning due to its simplicity in implementation and its robustness to incomplete and noisy data. Decision tree learning naturally requires the input attributes to be nominal (discrete). However, proper discretization of continuous-valued image features is a difficult task. In this paper, we present a decision tree based image semantic learning method, which avoids the difficult image feature discretization problem by making use of semantic template (ST) defined for each concept in our database. A ST is the representative feature of a concept, generated from the low-level features of a collection of …
Socio-Economic Impacts Of Computer Viruses In Tanzania, M Victor
Socio-Economic Impacts Of Computer Viruses In Tanzania, M Victor
Tanzania Journal of Engineering and Technology (TJET)
This paper reports on a research project conducted with an objective of identifying and assessing various approaches used by different computer users (Management, System Administrators and end users) in Tanzania to combat computer viruses (CVs), and to assess users' awareness level on CVs. Specifically, the study aimed at assessing the awareness level on CVs to the Tanzanian business community; analyze the socio -economic impact caused by CVs in Tanzania and; assess existing methods, capacity and limitations on controlling CVs in Tanzania. Data was collected using both questionnaires and interview from financial institutions such as NBC and BOT, and telecommunications sector …
Fuzzy Cognitive Goal Net For Interactive Storytelling Plot Design, Yundong Cai, Chunyan Miao, Ah-Hwee Tan, Zhiqi Shen
Fuzzy Cognitive Goal Net For Interactive Storytelling Plot Design, Yundong Cai, Chunyan Miao, Ah-Hwee Tan, Zhiqi Shen
Research Collection School Of Computing and Information Systems
Interactive storytelling attracts a lot of research interests among the interactive entertainments in recent years. Designing story plot for interactive storytelling is currently one of the most critical problems of interactive storytelling. Some traditional AI planning methods, such as Hierarchical Task Network, Heuristic Searching Method are widely used as the planning tool for the story plot design. This paper proposes a model called Fuzzy Cognitive Goal Net as the story plot planning tool for interactive storytelling, which combines the planning capability of Goal net and reasoning ability of Fuzzy Cognitive Maps. Compared to conventional methods, the proposed model shows a …
Poster Session A: Face Recognition Using Sub-Holistic Pca, Muhammad Murtaza Khan, Dr. Muhammad Younus Javed, Muhammad Almas Anjum
Poster Session A: Face Recognition Using Sub-Holistic Pca, Muhammad Murtaza Khan, Dr. Muhammad Younus Javed, Muhammad Almas Anjum
International Conference on Information and Communication Technologies
This paper proposes a face recognition scheme that enhances the correct face recognition rate as compared to conventional Principal Component Analysis (PCA). The proposed scheme, Sub-Holistic PCA (SH-PCA), was tested using ORL database and out performed PCA for all test scenarios. SH-PCA requires more computational power and memory as compared to PCA however it yields an improvement of 6% correct recognition on the complete ORL database of 400 images. The correct recognition rate for the complete ORL database is 90% for the SH-PCA technique.
Justilm: Few-Shot Justification Generation For Explainable Fact-Checking Of Real-World Claims, Fengzhu Zeng, Wei Gao
Justilm: Few-Shot Justification Generation For Explainable Fact-Checking Of Real-World Claims, Fengzhu Zeng, Wei Gao
Research Collection School Of Computing and Information Systems
Justification is an explanation that supports the verdict assigned to a claim in fact-checking. However, the task of justification generation is previously oversimplified as summarization of fact-check article authored by professional checkers. In this work, we propose a realistic approach to generate justification based on retrieved evidence. We present a new benchmark dataset called ExClaim for Explainable Claim verification, and introduce JustiLM, a novel few-shot retrieval-augmented language model to learn justification generation by leveraging fact-check articles as auxiliary resource during training. Our results show that JustiLM outperforms in-context learning (ICL)-enabled LMs including Flan-T5 and Llama2, and the retrieval-augmented model Atlas …
Towards Personalised Web Intelligence, Ah-Hwee Tan, Hwee-Leng Ong, Hong Pan, Jamie Ng, Qiu-Xiang Li
Towards Personalised Web Intelligence, Ah-Hwee Tan, Hwee-Leng Ong, Hong Pan, Jamie Ng, Qiu-Xiang Li
Research Collection School Of Computing and Information Systems
The Flexible Organizer for Competitive Intelligence (FOCI) is a personalised web intelligence system that provides an integrated platform for gathering, organising, tracking, and disseminating competitive information on the web. FOCI builds personalised information portfolios through a novel method called User-Configurable Clustering, which allows a user to personalise his/her portfolios in terms of the content as well as the organisational structure. This paper outlines the key challenges we face in personalised information management and gives a detailed account of FOCI’s underlying personalisation mechanism. For a quantitative evaluation of the system’s performance, we propose a set of performance indices based on information …
Review Of The Product Development Process And Information Flow In The Manufacturing Industry: Problems And A Possible Wav Forward, E Opiyo
Tanzania Journal of Engineering and Technology (TJET)
No abstract provided.
A Computer-Based Articulation Training Aid For Short Words (Cata), Mukund Devarajan
A Computer-Based Articulation Training Aid For Short Words (Cata), Mukund Devarajan
Electrical & Computer Engineering Theses & Dissertations
Several improvements in the vowel articulation training aid (VATA) are described, as well as the efforts to extend the visual feedback system to operate with short words in the form of consonant, vowel and consonant (CVC). The extended version of the visual feedback system is referred to as CATA (Computer-based Articulation Training Aid); the vowel version of the aid (VATA) only operates with ten American English monopthong vowels. Improvements in VATA include the use of a neural network (NN) recognizer method to prune a large database of vowel recordings to eliminate noisy and/or mispronounced tokens. The spectral jitter problem, previously …
On Machine Learning Methods For Chinese Document Classification, Ji He, Ah-Hwee Tan, Chew-Lim Tan
On Machine Learning Methods For Chinese Document Classification, Ji He, Ah-Hwee Tan, Chew-Lim Tan
Research Collection School Of Computing and Information Systems
This paper reports our comparative evaluation of three machine learning methods, namely k Nearest Neighbor (kNN), Support Vector Machines (SVM), and Adaptive Resonance Associative Map (ARAM) for Chinese document categorization. Based on two Chinese corpora, a series of controlled experiments evaluated their learning capabilities and efficiency in mining text classification knowledge. Benchmark experiments showed that their predictive performance were roughly comparable, especially on clean and well organized data sets. While kNN and ARAM yield better performances than SVM on small and clean data sets, SVM and ARAM significantly outperformed kNN on noisy data. Comparing efficiency, kNN was notably more costly …
Sistem Jadual Waktu Elektronik (Sjwe), Mohd Noh Mohd Nizam
Sistem Jadual Waktu Elektronik (Sjwe), Mohd Noh Mohd Nizam
Student Works (2000-2009)
Projek llmiah Tahap Akhir IT (WXES3182) ini merupakan salah satu keperluan kursus yang perlu diambil sebelum seseorang pelajar Ijazah Srujana Muda Sains Komputer itu bergelar graduan unversiti. Bagi tujuan itu saya telah membuat keputusan membina suatu sistem pentadbiran jadual waktu untuk FakuJti Sains Komputer & Teknologi Maklumat dan sistem ini saya namakan sebagai Sistem Jadual Waktu Elektronik (SJWE). SJWE ini dibangunkan oleh dua orang dan setiap orang membuat domain yang berlainan. Rakan saya Mohd. Sirhan Shabrani Bin Mt. Salleh membuat bahagian pentadbiran jadual waktu (Administration) di mana bahagian ini meliputi kerja-kerja yang perlu mempertimbangkan proses-proses yang perlu dijalankan sebelum suatu …
Knowledge Management Portal (Ai Department), Rahmat Nazariah
Knowledge Management Portal (Ai Department), Rahmat Nazariah
Student Works (2000-2009)
Portal pengurusan maklumat adalah satu sistem yang mana berfungsi sebagai tempat untuk mengumpul dan mencapai maklumat. Maklumat yang terdapat di dalam portal ini adalah maklumat yang terperinci tentang Jabatan Kepintaran Buatan, FSKTM, Universiti Malaya. Semua maklumat ini akan di olah kembali untuk mendapatkan sesuatu output yang berguna kepada pengguna sistem ini. Sistem portal pengurusan maklumat ini mengandungi dua modul utama iaitu Modul Pengguna Awam dan Modul Pentadbir. Modul pengguna awam membenarkan pengguna mencari informasi dan mencapai maklumat yang dipaparkan di dalam portal ini. Akan tetapi, capaian sebagai pengguna awam adalah agak terhad. Modul pihak pentadbir pula terdiri daripada 4 peringkat …
Side Collision Warning System For Transit Buses, Sue Mcneil, David Duggins, Christoph Mertz, Arne Suppe, Chuck Thorpe
Side Collision Warning System For Transit Buses, Sue Mcneil, David Duggins, Christoph Mertz, Arne Suppe, Chuck Thorpe
Research Collection School Of Computing and Information Systems
Transit buses are involved in many more accidents than other vehicles. Collision warning systems (CWS) are therefore placed most efficiently on these buses. In our project, we investigate their operating environment and available technologies to develop performance specifications for such CWS. The paper discusses our findings of transit buses driving through very cluttered surroundings and being involved in many different types of accidents where currently available CWS no not work effectively. One of the focuses of our work is pedestrians around the bus and their detection.
Cataloging Expert Systems: Optimism And Frustrated Reality, William Olmstadt
Cataloging Expert Systems: Optimism And Frustrated Reality, William Olmstadt
E-JASL: Electronic Journal of Academic and Special Librarianship (1999-2009, Volumes 1-10)
There is little question that computers have profoundly changed how information professionals work. The process of cataloging and classifying library materials was one of the first activities transformed by information technology. The introduction of the MARC format in the 1960s and the creation of national bibliographic utilities in the 1970s had a lasting impact on cataloging. In the 1980s, the affordability of microcomputers made the computer accessible for cataloging, even to small libraries. This trend toward automating library processes with computers parallels a broader societal interest in the use of computers to organize and store information. Following World War II, …
Homepage For Medical Image Processing, Nawot Nomansia
Homepage For Medical Image Processing, Nawot Nomansia
Student Works (2000-2009)
Homepage for Medical image Processing is a web site development project done to fulfills the requirement of Bachelor of Information Technology course. This homepage is about the current research in medical image processing area done by the research group in Neural Network Lab at Faculty of Computer Science and Intonation Technology University of Malaya. The architecture of this homepage based on client-server architecture model. Nowadays, many researchers use the Internet to storing, retrieving, and displaying information in a networked environment. Those who offer information through the Web must establish a homepage, a text and graphical screen display that usually welcomes …
Application Of Vibrational Techniques In Determination Of Dynamic Properties Of Agricultural Products-State Of The Arton Of Vibrational Techniques In Determination Of Dynamic Properties Of Agricultural Products-State Of The Art, Silas Kajuna
Tanzania Journal of Engineering and Technology (TJET)
Vibration is one of the techniques employed in the determination of dynamic properties of fruits and vegetables. It entails generation of a mechanical or acoustic vibrational signal which is propagated through the flesh of the agricultural material. A transducer is either attached or held close to the specimen to monitor the propagation of the signal through the specimen. The manner in which the signal is transmitted through the material is analyzed, and the dynamic properties of the specimen which relate to its firmness or its internal being are derived. The technique has been around for the past 30 years or …
The Effectiveness Of Expert Support Technology For Decision Making: Individuals Versus Small Groups, Fiona Fui-Hoon Nah, Jiye Mao, Izak Benbasat
The Effectiveness Of Expert Support Technology For Decision Making: Individuals Versus Small Groups, Fiona Fui-Hoon Nah, Jiye Mao, Izak Benbasat
Research Collection School Of Computing and Information Systems
Expert support systems (ESSs) are increasingly used in organizations to support individuals and groups in decision making. Although ESSs have been shown to enhance the decision-making capabilities of individuals, their benefits in supporting group decision making are less clear. To the best of our knowledge, no empirical research has evaluated the effectiveness of the technology in the group setting or compared its usefulness for supporting individual versus group decision making. The results of this research show that ESSs benefit decision making of both individuals and groups and novices are able to gain more from ESSs than experts. The findings also …
Some Developments In Information Technology In The Irish Hotel And Catering Industry, Sean Connell, Elaine Sunderland, Ciaran Mcdonnell
Some Developments In Information Technology In The Irish Hotel And Catering Industry, Sean Connell, Elaine Sunderland, Ciaran Mcdonnell
Conference papers
This paper describes the current and potential future use of computers in the Hospitality Industry in Ireland. It briefly outlines two research projects which are being carried out in the Dublin College of Catering in the application of computers to the Industry.