Open Access. Powered by Scholars. Published by Universities.®
- Discipline
-
- Physical Sciences and Mathematics (9387)
- Computer Sciences (9079)
- Databases and Information Systems (3569)
- Software Engineering (2223)
- Artificial Intelligence and Robotics (1929)
-
- Social and Behavioral Sciences (1630)
- Business (1307)
- Information Security (1122)
- Numerical Analysis and Scientific Computing (1061)
- Graphics and Human Computer Interfaces (958)
- Engineering (936)
- Theory and Algorithms (513)
- Computer Engineering (470)
- Economics (426)
- Operations Research, Systems Engineering and Industrial Engineering (425)
- Programming Languages and Compilers (413)
- Communication (348)
- OS and Networks (347)
- International and Area Studies (336)
- Asian Studies (327)
- Public Affairs, Public Policy and Public Administration (310)
- Education (295)
- Social Media (271)
- Finance and Financial Management (249)
- Environmental Sciences (240)
- Medicine and Health Sciences (230)
- Transportation (220)
- Econometrics (214)
- Technology and Innovation (201)
- Management Information Systems (187)
- Keyword
-
- Machine learning (149)
- Deep learning (130)
- Artificial intelligence (127)
- Singapore (125)
- Social media (82)
-
- Reinforcement learning (74)
- Privacy (71)
- Data mining (70)
- Security (63)
- Sustainability (61)
- Cloud computing (60)
- Deep Learning (58)
- Optimization (56)
- Empirical study (55)
- Software engineering (55)
- Blockchain (52)
- Natural language processing (52)
- Online learning (52)
- Visualization (52)
- Neural networks (50)
- Task analysis (50)
- Training (50)
- Anomaly detection (49)
- Large Language Models (49)
- Twitter (49)
- Collaboration (47)
- Machine Learning (47)
- Feature extraction (46)
- Algorithms (44)
- Semantics (44)
- Publication Year
- Publication
-
- Research Collection School Of Computing and Information Systems (8589)
- Research Collection Lee Kong Chian School Of Business (428)
- Research Collection School Of Economics (340)
- Dissertations and Theses Collection (Open Access) (272)
- Research Collection School of Social Sciences (193)
-
- Research Collection College of Integrative Studies (138)
- Research Collection Yong Pung How School Of Law (110)
- Research Collection School Of Accountancy (66)
- Asian Management Insights (63)
- Perspectives@SMU (49)
- Dissertations and Theses Collection (20)
- Research Collection Library (19)
- SMU Press Releases and News (18)
- Knowledge@SMU (17)
- FORCE 2026 (14)
- Sim Kee Boon Institute for Financial Economics (14)
- Research@SMU: Connecting the Dots (13)
- Social Space (12)
- MITB Thought Leadership Series (11)
- Research Collection School of Computing and Information Systems (11)
- Oral History Collection (9)
- Report to Stakeholders (9)
- PhD Student’s Publications Collection (8)
- LARC Research Publications (7)
- Research Collection School of Economics (7)
- Student Publications (7)
- Centre for Computational Law (2022-2025) (6)
- CCX Research (5)
- SMU Research Data (4)
- 2024 AI for Research Week (3)
- Publication Type
- File Type
Articles 8791 - 8820 of 10497
Full-Text Articles in Entire DC Network
Verifying Stateful Timed Csp Using Implicit Clocks And Zone Abstraction, Jun Sun, Yang Liu, Jin Song Dong, Xian Zhang
Verifying Stateful Timed Csp Using Implicit Clocks And Zone Abstraction, Jun Sun, Yang Liu, Jin Song Dong, Xian Zhang
Research Collection School Of Computing and Information Systems
In this work, we study model checking of compositional real-time systems. A system is modeled using mutable data variables as well as a compositional timed process. Instead of explicitly manipulating clock variables, a number of compositional timed behavioral patterns are used to capture quantitative timing requirements, e.g. delay, timeout, deadline, timed interrupt, etc. A fully automated abstraction technique is developed to build an abstract finite state machine from the model. The idea is to dynamically create/delete clocks, and maintain/solve a constraint on the clocks. The abstract machine weakly bi-simulates the model and, therefore, LTL model checking or trace-refinement checking are …
Changing The World, One Laptop At A Time, Knowledge@Smu
Changing The World, One Laptop At A Time, Knowledge@Smu
Knowledge@SMU
When Nicholas Negroponte mooted the idea of a US$100 laptop four years ago, he was met with scepticism. Undaunted, he and his team signed up partners and sponsors. Today, the end product, once described as “impossible”, is said to be inspiration behind netbooks. However, technological advancement was not the driving force behind the XO, as this laptop is called. Negroponte was motivated, instead, by the educational needs of developing nations, seeing that a large number of children in these countries receive little or no education. But just how far can inexpensive laptops go to address the needs of poverty-stricken communities?
Econometric Forecasting And High-Frequency Data Analysis, Yiu Kuen Tse, Yiu Kuen Tse
Econometric Forecasting And High-Frequency Data Analysis, Yiu Kuen Tse, Yiu Kuen Tse
Research Collection School of Economics
This important book consists of surveys of high-frequency financial data analysis and econometric forecasting, written by pioneers in these areas including Nobel laureate Lawrence Klein. Some of the chapters were presented as tutorials to an audience in the Econometric Forecasting and High-Frequency Data Analysis Workshop at the Institute for Mathematical Science, National University of Singapore in May 2006. They will be of interest to researchers working in macroeconometrics as well as financial econometrics. Moreover, readers will find these chapters useful as a guide to the literature as well as suggestions for future research.
Emotional Labor Demands, Wages And Gender: A Within-Person, Between-Jobs Study, Devasheesh P. Bhave, Theresa M. Glomb
Emotional Labor Demands, Wages And Gender: A Within-Person, Between-Jobs Study, Devasheesh P. Bhave, Theresa M. Glomb
Research Collection Lee Kong Chian School Of Business
Although research suggests the important role of gender in emotional labour, its effect on the relationship between emotional labour demands and wages has not been examined explicitly. The current study investigates this relationship by testing hypotheses derived from theories of vocational choice and labour market supply and demand. Hypotheses are tested using a unique within-person, between-jobs longitudinal dataset with information on two jobs for each worker in a national sample of U.S. workers (N=5,488). After controlling for relevant variables related to wages, results suggest men incur wage penalties of approximately 6% when moving to occupations with higher emotional labour demands. …
Batch Mode Active Learning With Applications To Text Categorization And Image Retrieval, Steven C. H. Hoi, Rong Jin, Michael R. Lyu
Batch Mode Active Learning With Applications To Text Categorization And Image Retrieval, Steven C. H. Hoi, Rong Jin, Michael R. Lyu
Research Collection School Of Computing and Information Systems
Most machine learning tasks in data classification and information retrieval require manually labeled data examples in the training stage. The goal of active learning is to select the most informative examples for manual labeling in these learning tasks. Most of the previous studies in active learning have focused on selecting a single unlabeled example in each iteration. This could be inefficient, since the classification model has to be retrained for every acquired labeled example. It is also inappropriate for the setup of information retrieval tasks where the user's relevance feedback is often provided for the top K retrieved items. In …
Detecting Automotive Exhaust Gas Based On Fuzzy Inference System, Li. Shujin, Ming Bai, Quan Wang, Bo Chen, Xiaobing Zhao, Ting Yang, Zhaoxia Wang
Detecting Automotive Exhaust Gas Based On Fuzzy Inference System, Li. Shujin, Ming Bai, Quan Wang, Bo Chen, Xiaobing Zhao, Ting Yang, Zhaoxia Wang
Research Collection School Of Computing and Information Systems
This paper proposes a method of detecting automotive exhaust gas based on fuzzy logic inference after analyzing the principle of the infrared automobile exhaust gas analyzer and the influence of the environmental temperature on analyzer. This paper analyses the measurement error caused by environmental temperature, and then makes a non-linear error correction of temperature for the infrared sensor using fuzzy inference. The results of simulation have clearly demonstrated that the proposed fuzzy compensation scheme is better than the non-fuzzy method.
Efficient Conditional Proxy Re-Encryption With Chosen-Ciphertext Security, Jian Weng, Yanjiang Yang, Qiang Tang, Robert H. Deng
Efficient Conditional Proxy Re-Encryption With Chosen-Ciphertext Security, Jian Weng, Yanjiang Yang, Qiang Tang, Robert H. Deng
Research Collection School Of Computing and Information Systems
Recently, a variant of proxy re-encryption, named conditional proxy re-encryption (C-PRE), has been introduced. Compared with traditional proxy re-encryption, C-PRE enables the delegator to implement fine-grained delegation of decryption rights, and thus is more useful in many applications. In this paper, based on a careful observation on the existing definitions and security notions for C-PRE, we re-formalize more rigorous definition and security notions for C-PRE. We further propose a more efficient C-PRE scheme, and prove its chosen-ciphertext security under the decisional bilinear Diffie-Hellman (DBDH) assumption in the random oracle model. In addition, we point out that a recent C-PRE scheme …
Hierarchical Self-Healing Key Distribution For Heterogeneous Wireless Sensor Networks, Yanjiang Yang, Jianying Zhou, Robert H. Deng, Feng Bao
Hierarchical Self-Healing Key Distribution For Heterogeneous Wireless Sensor Networks, Yanjiang Yang, Jianying Zhou, Robert H. Deng, Feng Bao
Research Collection School Of Computing and Information Systems
Self-healing group key distribution aims to achieve robust key distribution over lossy channels in wireless sensor networks (WSNs). However, all existing self-healing group key distribution schemes in the literature consider homogenous WSNs which are known to be unscalable. Heterogeneous WSNs have better scalability and performance than homogenous ones. We are thus motivated to study hierarchial self-healing group key distribution, tailored to the heterogeneous WSN architecture. In particular, we revisit and adapt Dutta et al.’s model to the setting of hierarchical self-healing group key distribution, and propose a concrete scheme that achieves computational security and high efficiency.
Font Size: Make Font Size Smaller Make Font Size Default Make Font Size Larger Exploiting Coordination Locales In Distributed Pomdps Via Social Model Shaping, Pradeep Varakantham, Jun Young Kwak, Matthew Taylor, Janusz Marecki, Paul Scerri, Milind Tambe
Font Size: Make Font Size Smaller Make Font Size Default Make Font Size Larger Exploiting Coordination Locales In Distributed Pomdps Via Social Model Shaping, Pradeep Varakantham, Jun Young Kwak, Matthew Taylor, Janusz Marecki, Paul Scerri, Milind Tambe
Research Collection School Of Computing and Information Systems
Distributed POMDPs provide an expressive framework for modeling multiagent collaboration problems, but NEXPComplete complexity hinders their scalability and application in real-world domains. This paper introduces a subclass of distributed POMDPs, and TREMOR, an algorithm to solve such distributed POMDPs. The primary novelty of TREMOR is that agents plan individually with a single agent POMDP solver and use social model shaping to implicitly coordinate with other agents. Experiments demonstrate that TREMOR can provide solutions orders of magnitude faster than existing algorithms while achieving comparable, or even superior, solution quality.
Communication-Efficient Classification In P2p Networks, Hock Hee Ang, Vivekanand Gopalkrishnan, Wee Keong Ng, Steven C. H. Hoi
Communication-Efficient Classification In P2p Networks, Hock Hee Ang, Vivekanand Gopalkrishnan, Wee Keong Ng, Steven C. H. Hoi
Research Collection School Of Computing and Information Systems
Distributed classification aims to learn with accuracy comparable to that of centralized approaches but at far lesser communication and computation costs. By nature, P2P networks provide an excellent environment for performing a distributed classification task due to the high availability of shared resources, such as bandwidth, storage space, and rich computational power. However, learning in P2P networks is faced with many challenging issues; viz., scalability, peer dynamism, asynchronism and fault-tolerance. In this paper, we address these challenges by presenting CEMPaR—a communication-efficient framework based on cascading SVMs that exploits the characteristics of DHT-based lookup protocols. CEMPaR is designed to be robust …
Accelerating Sequence Searching: Dimensionality Reduction Method, Guojie Song, Bin Cui, Baihua Zheng, Kunqing Xie, Dongqing Yang
Accelerating Sequence Searching: Dimensionality Reduction Method, Guojie Song, Bin Cui, Baihua Zheng, Kunqing Xie, Dongqing Yang
Research Collection School Of Computing and Information Systems
Similarity search over long sequence dataset becomes increasingly popular in many emerging applications, such as text retrieval, genetic sequences exploring, etc. In this paper, a novel index structure, namely Sequence Embedding Multiset tree (SEM − tree), has been proposed to speed up the searching process over long sequences. The SEM-tree is a multi-level structure where each level represents the sequence data with different compression level of multiset, and the length of multiset increases towards the leaf level which contains original sequences. The multisets, obtained using sequence embedding algorithms, have the desirable property that they do not need to keep the …
Visible Reverse K-Nearest Neighbor Query Processing In Spatial Databases, Yunjun Gao, Baihua Zheng, Gencai Chen, Wang-Chien Lee, Ken C. K. Lee, Qing Li
Visible Reverse K-Nearest Neighbor Query Processing In Spatial Databases, Yunjun Gao, Baihua Zheng, Gencai Chen, Wang-Chien Lee, Ken C. K. Lee, Qing Li
Research Collection School Of Computing and Information Systems
Reverse nearest neighbor (RNN) queries have a broad application base such as decision support, profile-based marketing, resource allocation, etc. Previous work on RNN search does not take obstacles into consideration. In the real world, however, there are many physical obstacles (e.g., buildings) and their presence may affect the visibility between objects. In this paper, we introduce a novel variant of RNN queries, namely, visible reverse nearest neighbor (VRNN) search, which considers the impact of obstacles on the visibility of objects. Given a data set P, an obstacle set O, and a query point q in a 2D space, a VRNN …
Localized Matching Using Earth Mover's Distance Towards Discovery Of Common Patterns From Small Image Samples, Hung-Khoon Tan, Chong-Wah Ngo
Localized Matching Using Earth Mover's Distance Towards Discovery Of Common Patterns From Small Image Samples, Hung-Khoon Tan, Chong-Wah Ngo
Research Collection School Of Computing and Information Systems
This paper proposes a new approach for the discovery of common patterns in a small set of images by region matching. The issues in feature robustness, matching robustness and noise artifact are addressed to delve into the potential of using regions as the basic matching unit. We novelly employ the many-to-many (M2M) matching strategy, specifically with the Earth Mover's Distance (EMD), to increase resilience towards the structural inconsistency from improper region segmentation. However, the matching pattern of M2M is dispersed and unregulated in nature, leading to the challenges of mining a common pattern while identifying the underlying transformation. To avoid …
A Latent Model For Visual Disambiguation Of Keyword-Based Image Search, Kong-Wah Wan, Ah-Hwee Tan, Joo-Hwee Lim, Liang-Tien Chia, Sujoy Roy
A Latent Model For Visual Disambiguation Of Keyword-Based Image Search, Kong-Wah Wan, Ah-Hwee Tan, Joo-Hwee Lim, Liang-Tien Chia, Sujoy Roy
Research Collection School Of Computing and Information Systems
The problem of polysemy in keyword-based image search arises mainly from the inherent ambiguity in user queries. We propose a latent model based approach that resolves user search ambiguity by allowing sense specific diversity in search results. Given a query keyword and the images retrieved by issuing the query to an image search engine, we first learn a latent visual sense model of these polysemous images. Next, we use Wikipedia to disambiguate the word sense of the original query, and issue these Wiki-senses as new queries to retrieve sense specific images. A sense-specific image classifier is then learnt by combining …
Multi-View Ear Recognition Based On Moving Least Square Pose Interpolation, Heng Liu, David Zhang, Zhiyuan Zhang
Multi-View Ear Recognition Based On Moving Least Square Pose Interpolation, Heng Liu, David Zhang, Zhiyuan Zhang
Research Collection School Of Computing and Information Systems
Based on moving least square, a multi-view ear pose interpolation and corresponding recognition approach is proposed. This work firstly analyzes the shape characteristics of actual trace caused by ear pose varying in feature space. Then according to training samples pose projection, we manage to recover the complete multi-view ear pose manifold by using moving least square pose interpolation. The constructed multi-view ear pose manifolds can be easily utilized to recognize ear images captured under different views based on finding the minimal projection distance to the manifolds. The experimental results and some comparisons show the new method is superior to manifold …
Understanding Early Diffusion Of Digital Wireless Phones, Robert J. Kauffman, Angsana A. Techatassanasoontorn
Understanding Early Diffusion Of Digital Wireless Phones, Robert J. Kauffman, Angsana A. Techatassanasoontorn
Research Collection School Of Computing and Information Systems
There is increasing empirical evidence from academic research and strong recognition among policymakers that wide diffusion and innovative uses of digital wireless phones are important sources of a country's economic growth and social development. Adopters do not necessarily adopt digital wireless phones at the same time though. Although the diffusion of innovation theory suggests five adopter categories according to their degree of innovativeness, this approach lacks theoretical justification and, more importantly, it makes a critical assumption of a normal distribution of adopters that needs empirical validation. This study investigates the basis for defining different adopter categories and factors that affect …
Why Quants Fail, M. Thulasidas
Why Quants Fail, M. Thulasidas
Research Collection School Of Computing and Information Systems
Mathematical finance is built on a couple of assumptions. The most fundamental of them is the one on ma ket efficiency. It states that the market prices every asset fairly, and that the prices contain all the information available in the market.
A Hybrid Firm's Pricing Strategy In Electronic Commerce Under Channel Migration, Robert John Kauffman, Dongwon Lee, Jung Lee, Byungjoon Yoo
A Hybrid Firm's Pricing Strategy In Electronic Commerce Under Channel Migration, Robert John Kauffman, Dongwon Lee, Jung Lee, Byungjoon Yoo
Research Collection School Of Computing and Information Systems
Achieving an effective business design across the Internet and the off-line channel is a critical concern for a hybrid firm's choice of pricing strategy. Two pricing models are proposed to examine how consumer channel migration (one-way channel interaction from the traditional sales channel to the Internet) affects pricing strategy. One model has no interaction between the Internet and off-line channels. The other includes the possibility of one-way migration to the Internet channel and incorporates consumers' channel-switching costs and loyalty to the firm. The two models offer interesting results for understanding traditional and Internet-based selling. A high level of channel migration …
Admission Control For Differentiated Services In Future Generation Cdma Networks, Hwee-Pink Tan, Rudesindo Núñez-Queija, Adriana F. Gabor, Onno J. Boxma
Admission Control For Differentiated Services In Future Generation Cdma Networks, Hwee-Pink Tan, Rudesindo Núñez-Queija, Adriana F. Gabor, Onno J. Boxma
Research Collection School Of Computing and Information Systems
Future Generation CDMA wireless systems, e.g., 3G, can simultaneously accommodate flow transmissions of users with widely heterogeneous applications. As radio resources are limited, we propose an admission control rule that protects users with stringent transmission bit-rate requirements (“streaming traffic”) while offering sufficient capacity over longer time intervals to delay-tolerant users (“elastic traffic”). While our strategy may not satisfy classical notions of fairness, we aim to reduce congestion and increase overall throughput of elastic users. Using time-scale decomposition, we develop approximations to evaluate the performance of our differentiated admission control strategy to support integrated services with transmission bit-rate requirements in a …
Exploiting Bilingual Information To Improve Web Search, Wei Gao, John Bitzer, Ming Zhou, Kam-Fai Wong
Exploiting Bilingual Information To Improve Web Search, Wei Gao, John Bitzer, Ming Zhou, Kam-Fai Wong
Research Collection School Of Computing and Information Systems
Web search quality can vary widely across languages, even for the same information need. We propose to exploit this variation in quality by learning a ranking function on bilingual queries: queries that appear in query logs for two languages but represent equivalent search interests. For a given bilingual query, along with corresponding monolingual query log and monolingual ranking, we generate a ranking on pairs of documents, one from each language. Then we learn a linear ranking function which exploits bilingual features on pairs of documents, as well as standard monolingual features. Finally, we show how to reconstruct monolingual ranking from …
Are Male And Female Avatars Perceived Equally In 3-D Virtual Worlds?, David Dewester, Fiona Fui-Hoon Nah, Sarah Gervais, Keng Siau
Are Male And Female Avatars Perceived Equally In 3-D Virtual Worlds?, David Dewester, Fiona Fui-Hoon Nah, Sarah Gervais, Keng Siau
Research Collection School Of Computing and Information Systems
Virtual worlds are three-dimensional, computer-generated worlds in which users take the form of avatars and use those avatars to interact with objects and other avatars in the virtual world. Virtual worlds are growing in importance in both educational institutions and businesses. Educational institutions have adopted virtual worlds as a medium for instructional delivery whereas businesses are using virtual worlds for recruitment, training, collaboration, and marketing. Given these emerging phenomena, a better understanding of behavioral and perceptual issues in virtual worlds is warranted. We propose a research model to study the interaction effects of gender stereotypicality of male and female avatars …
Multilayer Image Inpainting Approach Based On Neural Networks, Quan Wang, Zhaoxia Wang, Che Sau Chang, Ting Yang
Multilayer Image Inpainting Approach Based On Neural Networks, Quan Wang, Zhaoxia Wang, Che Sau Chang, Ting Yang
Research Collection School Of Computing and Information Systems
This paper describes an image inpainting approach based on the self-organizing map for dividing an image into several layers, assigning each damaged pixel to one layer, and then restoring these damaged pixels by the information of their respective layer. These inpainted layers are then fused together to provide the final inpainting results. This approach takes advantage of the neural network's ability of imitating human's brain to separate objects of an image into different layers for inpainting. The approach is promising as clearly demonstrated by the results in this paper.
Essential Spreadsheet Modeling Course For Business Students, Thin Yin Leong, Michelle L. F. Cheong
Essential Spreadsheet Modeling Course For Business Students, Thin Yin Leong, Michelle L. F. Cheong
Research Collection School Of Computing and Information Systems
Ask any student at the Singapore Management University (SMU) to name one of the most practical and useful courses offered by the university. The answer would inevitably include CAT. CAT stands for the "Computer as an Analysis Tool" course. Originally based on a course of the same title offered by the Wharton Business School, the focus of CAT was shifted to provide business students the essential practical skills and necessary "real-world" exposure to better use personal computers for resolving business problems. The course is basically centered on using the Excel spreadsheet to work on ambiguous ill-defined problems.
Game Action Based Power Management For Multiplayer Online Game, Bhojan Anand, A. L. Ananda, Mun Choon Chan, Long Thanh Le, Rajesh Krishna Balan
Game Action Based Power Management For Multiplayer Online Game, Bhojan Anand, A. L. Ananda, Mun Choon Chan, Long Thanh Le, Rajesh Krishna Balan
Research Collection School Of Computing and Information Systems
Current mobile devices embrace a wide range of functionalities including high speed network support, hardware accelerated 3D graphics, and multimedia capabilities. These capabilities have boosted the interest for enabling multiplayer online games (MOG) support on such devices. However, the lack of similar growth in battery technology limits the usability of these devices for MOGs. In this paper, we present energy conservation techniques for highly interactive MOGs. These are games, such as first-person shooters, where crisp user interaction is paramount to the overall game experience. Hence, conserving energy while preserving crisp user interaction becomes a critical consideration in this domain. We …
Multi-Task Transfer Learning For Weakly-Supervised Relation Extraction, Jing Jiang
Multi-Task Transfer Learning For Weakly-Supervised Relation Extraction, Jing Jiang
Research Collection School Of Computing and Information Systems
Creating labeled training data for relation extraction is expensive. In this paper, we study relation extraction in a special weakly-supervised setting when we have only a few seed instances of the target relation type we want to extract but we also have a large amount of labeled instances of other relation types. Observing that different relation types can share certain common structures, we propose to use a multi-task learning method coupled with human guidance to address this weakly-supervised relation extraction problem. The proposed framework models the commonality among different relation types through a shared weight vector, enables knowledge learned from …
Ssnetviz: A Visualization Engine For Heterogeneous Semantic Social Networks, Ee Peng Lim, Maureen Maureen, Nelman Lubis Ibrahim, Aixin Sun, Anwitaman Datta, Kuiyu Chang
Ssnetviz: A Visualization Engine For Heterogeneous Semantic Social Networks, Ee Peng Lim, Maureen Maureen, Nelman Lubis Ibrahim, Aixin Sun, Anwitaman Datta, Kuiyu Chang
Research Collection School Of Computing and Information Systems
SSnetViz is an ongoing research to design and implement a visualization engine for heterogeneous semantic social networks. A semantic social network is a multi-modal network that contains nodes representing di®erent types of people or object entities, and edges representing relationships among them. When multiple heterogeneous semantic social networks are to be visualized together, SSnetViz provides a suite of functions to store heterogeneous semantic social networks, to integrate them for searching and analysis. We will illustrate these functions using social networks related to terrorism research, one crafted by domain experts and another from Wikipedia.
Extracting Paraphrases Of Technical Terms From Noisy Parallel Software Corpus, Xiaoyin Wang, David Lo, Jing Jiang, Lu Zhang, Hong Mei
Extracting Paraphrases Of Technical Terms From Noisy Parallel Software Corpus, Xiaoyin Wang, David Lo, Jing Jiang, Lu Zhang, Hong Mei
Research Collection School Of Computing and Information Systems
In this paper, we study the problem of extracting technical paraphrases from a parallel software corpus, namely, a collection of duplicate bug reports. Paraphrase acquisition is a fundamental task in the emerging area of text mining for software engineering. Existing paraphrase extraction methods are not entirely suitable here due to the noisy nature of bug reports. We propose a number of techniques to address the noisy data problem. The empirical evaluation shows that our method significantly improves an existing method by upto 58%
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 …
3-D Virtual Worlds And Higher Education, X. Chen, Keng Siau, Fiona Fui-Hoon Nah
3-D Virtual Worlds And Higher Education, X. Chen, Keng Siau, Fiona Fui-Hoon Nah
Research Collection School Of Computing and Information Systems
Conducting education in three-dimensional (3-D) virtual worlds is an emerging phenomenon in the educational arena. The objective of this research is to investigate the factors influencing students’ intention to adopt the 3-D virtual worlds for delivery of education. Drawing on existing technology acceptance models as well as studies in traditional and distance education, we developed a model to study students’ acceptance of using a 3-D virtual world for education and propose to test the model empirically using survey data collected from college students. We also study the use of two instructional methods in the 3-D virtual world. This study contributes …
Measuring Method Complexity: Uml Versus Bpmn, Jan Recker, Michael Zur Muehlen, Keng Siau, John Erickson, Marta Indulska
Measuring Method Complexity: Uml Versus Bpmn, Jan Recker, Michael Zur Muehlen, Keng Siau, John Erickson, Marta Indulska
Research Collection School Of Computing and Information Systems
Graphical models are used to depict relevant aspects of real-world domains intended to be supported by an information system. Various approaches for modeling exist and approaches such as object-oriented and process-oriented modeling methods are in widespread use. These modeling methods differ in their expressive power as well as in their complexity of use, thereby leading to an important investment decision for organizations seeking to conduct modeling projects. In this paper, we used an established approach for evaluating the complexity of conceptual modeling methods and compared two important industry standards for modeling, Unified Modeling Language and Business Process Modeling Notation, based …