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Articles 6571 - 6600 of 8479
Full-Text Articles in Computer Sciences
Robust Distributed Scheduling Via Time Period Aggregation, Shih-Fen Cheng, John Tajan, Hoong Chuin Lau
Robust Distributed Scheduling Via Time Period Aggregation, Shih-Fen Cheng, John Tajan, Hoong Chuin Lau
Research Collection School Of Computing and Information Systems
In this paper, we evaluate whether the robustness of a market mechanism that allocates complementary resources could be improved through the aggregation of time periods in which resources are consumed. In particular, we study a multi-round combinatorial auction that is built on a general equilibrium framework. We adopt the general equilibrium framework and the particular combinatorial auction design from the literature, and we investigate the benefits and the limitation of time-period aggregation when demand-side uncertainties are introduced. By using simulation experiments on a real-life resource allocation problem from a container port, we show that, under stochastic conditions, the performance variation …
Dynamic Secure Cloud Storage With Provenance, Sherman S. M. Chow, Cheng-Kang Chu, Xinyi Huang, Jianying Zhou, Robert H. Deng
Dynamic Secure Cloud Storage With Provenance, Sherman S. M. Chow, Cheng-Kang Chu, Xinyi Huang, Jianying Zhou, Robert H. Deng
Research Collection School Of Computing and Information Systems
One concern in using cloud storage is that the sensitive data should be confidential to the servers which are outside the trust domain of data owners. Another issue is that the user may want to preserve his/her anonymity in the sharing or accessing of the data (such as in Web 2.0 applications). To fully enjoy the benefits of cloud storage, we need a confidential data sharing mechanism which is fine-grained (one can specify who can access which classes of his/her encrypted files), dynamic (the total number of users is not fixed in the setup, and any new user can decrypt …
Information Extraction From Text, Jing Jiang
Information Extraction From Text, Jing Jiang
Research Collection School Of Computing and Information Systems
Information extraction is the task of finding structured information from unstructured or semi-structured text. It is an important task in text mining and has been extensively studied in various research communities including natural language processing, information retrieval and Web mining. It has a wide range of applications in domains such as biomedical literature mining and business intelligence. Two fundamental tasks of information extraction are named entity recognition and relation extraction. The former refers to finding names of entities such as people, organizations and locations. The latter refers to finding the semantic relations such as FounderOf and HeadquarteredIn between entities. In …
Preface: Trends In Natural And Machine Intelligence, Jonathan H. Chan, Ah-Hwee Tan
Preface: Trends In Natural And Machine Intelligence, Jonathan H. Chan, Ah-Hwee Tan
Research Collection School Of Computing and Information Systems
Trends in natural and machine intelligence are increasingly reflecting a convergence in these two well-established fields of study. The Third International Neural Network Society Winter Conference (INNS-WC 2012) was held in Bangkok, Thailand, on October 3-5, 2012. INNS-WC2012, with an aim to bring together scientists, practitioners, and students worldwide, to discuss the past, present, and future challenges and trends in the area of natural and machine intelligence. This event has been a bi-annual conference of the International Neural Network Society (INNS) to provide a forum for international researchers to exchange latest ideas and advances on neural networks and related discipline.
An Improved K-Nearest-Neighbor Algorithm For Text Categorization, Shengyi Jiang, Guansong Pang, Meiling Wu, Limin Kuang
An Improved K-Nearest-Neighbor Algorithm For Text Categorization, Shengyi Jiang, Guansong Pang, Meiling Wu, Limin Kuang
Research Collection School Of Computing and Information Systems
Text categorization is a significant tool to manage and organize the surging text data. Many text categorization algorithms have been explored in previous literatures, such as KNN, Naive Bayes and Support Vector Machine. KNN text categorization is an effective but less efficient classification method. In this paper, we propose an improved KNN algorithm for text categorization, which builds the classification model by combining constrained one pass clustering algorithm and KNN text categorization. Empirical results on three benchmark corpora show that our algorithm can reduce the text similarity computation substantially and outperform the-state-of-the-art KNN, Naive Bayes and Support Vector Machine classifiers. …
Mining Diversity On Social Media Networks, Lu Liu, Feida Zhu, Meng Jiang, Jiawei Han, Lifeng Sun, Shiqiang Yang
Mining Diversity On Social Media Networks, Lu Liu, Feida Zhu, Meng Jiang, Jiawei Han, Lifeng Sun, Shiqiang Yang
Research Collection School Of Computing and Information Systems
The fast development of multimedia technology and increasing availability of network bandwidth has given rise to an abundance of network data as a result of all the ever-booming social media and social websites in recent years, e.g., Flickr, Youtube, MySpace, Facebook, etc. Social network analysis has therefore become a critical problem attracting enthusiasm from both academia and industry. However, an important measure that captures a participant’s diversity in the network has been largely neglected in previous studies. Namely, diversity characterizes how diverse a given node connects with its peers. In this paper, we give a comprehensive study of this concept. …
Imbalance Challenge Of Enacting Information Privacy Safeguards In Healthcare: A Grounded Theory Approach, Rachida Parks, Heng Xu, Chao-Hsien Chu
Imbalance Challenge Of Enacting Information Privacy Safeguards In Healthcare: A Grounded Theory Approach, Rachida Parks, Heng Xu, Chao-Hsien Chu
Research Collection School Of Computing and Information Systems
Healthcare organizations face significant challenges in designing and implementing the appropriate safeguards to mitigate information privacy threats. While many studies examined various technical and behavioral safeguards to protect the confidentiality and privacy of patient information, very little is known about the actual outcomes and implications of the privacy practices in which organizations engage. There is little research theoretically explaining the outcomes of enacting privacy safeguards and subsequent effects on privacy compliance. This paper reports the results of a grounded theory study investigating the intended consequences (positive impacts) and unintended (negative impacts) consequences of enacting privacy safeguards in healthcare organizations. An …
Topic Based Query Suggestions For Video Search, Kong-Wah Wan, Ah-Hwee Tan, Joo-Hwee Lim, Liang-Tien Chia
Topic Based Query Suggestions For Video Search, Kong-Wah Wan, Ah-Hwee Tan, Joo-Hwee Lim, Liang-Tien Chia
Research Collection School Of Computing and Information Systems
Query suggestion is an assistive technology mechanism commonly used in search engines to enable a user to formulate their search queries by predicting or completing the next few query words that the user is likely to type. In most implementations, the suggestions are mined from query log and use some simple measure of query similarity such as query frequency or lexicographical matching. In this paper, we propose an alternative method of presenting query suggestions by their thematic topics. Our method adopts a document-centric approach to mine topics in the corpus, and does not require the availability of a query log. …
Self‐Regulating Action Exploration In Reinforcement Learning, Teck-Hou Teng, Ah-Hwee Tan, Yuan-Sin Tan
Self‐Regulating Action Exploration In Reinforcement Learning, Teck-Hou Teng, Ah-Hwee Tan, Yuan-Sin Tan
Research Collection School Of Computing and Information Systems
The basic tenet of a learning process is for an agent to learn for only as much and as long as it is necessary. With reinforcement learning, the learning process is divided between exploration and exploitation. Given the complexity of the problem domain and the randomness of the learning process, the exact duration of the reinforcement learning process can never be known with certainty. Using an inaccurate number of training iterations leads either to the non-convergence or the over-training of the learning agent. This work addresses such issues by proposing a technique to self-regulate the exploration rate and training duration …
Multi-Party Multi-Period Supply Chain Coordination, Thin Yin Leong, Michelle Lee Fong Cheong
Multi-Party Multi-Period Supply Chain Coordination, Thin Yin Leong, Michelle Lee Fong Cheong
Research Collection School Of Computing and Information Systems
We apply combinatorial auction as a coordination mechanism to smooth demands placed on suppliers' limited production capacities, allowing several manufacturers to share common suppliers effectively. Products are bidders bidding for parts from suppliers, consuming their capacities in different time periods. The fourth party logistic (4PL) provider acts as the auctioneer to coordinate bids and perform price iterations. We leverage on the strong links between the Lagrangian relaxation method and combinatorial auction, where the Lagrange multipliers serve as the supply capacity reserve prices, to balance the demand and supply of capacities. To prevent cyclic behaviour and to increase convergence speed, we …
A Sentiment Analysis Of Singapore Presidential Election 2011 Using Twitter Data With Census Correction, Murphy Junyu Choy, Michelle Lee Fong Cheong, Nang Laik Ma, Ping Shung Koo
A Sentiment Analysis Of Singapore Presidential Election 2011 Using Twitter Data With Census Correction, Murphy Junyu Choy, Michelle Lee Fong Cheong, Nang Laik Ma, Ping Shung Koo
Research Collection School Of Computing and Information Systems
Sentiment analysis is a new area in text analytics where it focuses on the analysis and understanding of the human emotions from the text patterns. This new form of analysis has been widely adopted in customer relationship management especially in the context of complaint management. However, sentiment analysis using Twitter data has remained extremely difficult to manage due to sampling biasness. In this paper, we will discuss about the application of reweighting techniques in conjunction with online sentiment divisions to predict the vote percentage that individual presidential candidate in Singapore will receive in the Presidential Election 2011. There will be …
Robust Local Search For Solving Rcpsp/Max With Durational Uncertainty, Na Fu, Hoong Chuin Lau, Pradeep Varakantham, Fei Xiao
Robust Local Search For Solving Rcpsp/Max With Durational Uncertainty, Na Fu, Hoong Chuin Lau, Pradeep Varakantham, Fei Xiao
Research Collection School Of Computing and Information Systems
Scheduling problems in manufacturing, logistics and project management have frequently been modeled using the framework of Resource Constrained Project Scheduling Problems with minimum and maximum time lags (RCPSP/max). Due to the importance of these problems, providing scalable solution schedules for RCPSP/max problems is a topic of extensive research. However, all existing methods for solving RCPSP/max assume that durations of activities are known with certainty, an assumption that does not hold in real world scheduling problems where unexpected external events such as manpower availability, weather changes, etc. lead to delays or advances in completion of activities. Thus, in this paper, our …
A Survey On Privacy Frameworks For Rfid Authentication, Chunhua Su, Yingjiu Li, Yunlei Zhao, Robert H. Deng, Yiming Zhao, Jianying Zhou
A Survey On Privacy Frameworks For Rfid Authentication, Chunhua Su, Yingjiu Li, Yunlei Zhao, Robert H. Deng, Yiming Zhao, Jianying Zhou
Research Collection School Of Computing and Information Systems
Due to rapid growth of RFID system applications, the security and privacy problems become more and more important to guarantee the validity of RFID systems. Without introducing proper privacy protection mechanisms, widespread deployment of RFID could raise privacy concerns to both companies and individuals. As a fundamental issue for the design and analysis of secure RFID systems, some formal RFID privacy frameworks were proposed in recent years to give the principles for evaluating the security and privacy in RFID system. However, readers can be confused with so many proposed frameworks. In this paper, we make a comparative and survey study …
Who Is Retweeting The Tweeters? Modeling, Originating, And Promoting Behaviors In The Twitter Network, Achananuparp Palakorn, Ee Peng Lim, Jing Jiang, Tuan Anh Hoang
Who Is Retweeting The Tweeters? Modeling, Originating, And Promoting Behaviors In The Twitter Network, Achananuparp Palakorn, Ee Peng Lim, Jing Jiang, Tuan Anh Hoang
Research Collection School Of Computing and Information Systems
Real-time microblogging systems such as Twitter offer users an easy and lightweight means to exchange information. Instead of writing formal and lengthy messages, microbloggers prefer to frequently broadcast several short messages to be read by other users. Only when messages are interesting, are they propagated further by the readers. In this article, we examine user behavior relevant to information propagation through microblogging. We specifically use retweeting activities among Twitter users to define and model originating and promoting behavior. We propose a basic model for measuring the two behaviors, a mutual dependency model, which considers the mutual relationships between the two …
Evaluating The Use Of A Mobile Annotation System For Geography Education, Dion Hoe-Lian Goh, Khasfariyati Razikin, Chei Sian Lee, Ee Peng Lim, Kalyani Chatterjea, Chew-Hung Chang
Evaluating The Use Of A Mobile Annotation System For Geography Education, Dion Hoe-Lian Goh, Khasfariyati Razikin, Chei Sian Lee, Ee Peng Lim, Kalyani Chatterjea, Chew-Hung Chang
Research Collection School Of Computing and Information Systems
Mobile devices used in educational settings are usually employed within a collaborative learning activity in which learning takes place in the form of social interactions between team members while performing a shared task. The authors aim to introduce MobiTOP (Mobile Tagging of Objects and People), a mobile annotation system that allows users to contribute and share geospatial multimedia annotations via mobile devices. Field observations and interviews were conducted. A group of trainee teachers involved in a geography field study were instructed to identify rock formations by collaborating with each other using the MobiTOP system. The trainee teachers who were in …
Road: A New Spatial Object Search Framework For Road Networks, Ken C. K. Lee, Wang-Chien Lee, Baihua Zheng, Yuan Tian
Road: A New Spatial Object Search Framework For Road Networks, Ken C. K. Lee, Wang-Chien Lee, Baihua Zheng, Yuan Tian
Research Collection School Of Computing and Information Systems
In this paper, we present a new system framework called ROAD for spatial object search on road networks. ROAD is extensible to diverse object types and efficient for processing various location-dependent spatial queries (LDSQs), as it maintains objects separately from a given network and adopts an effective search space pruning technique. Based on our analysis on the two essential operations for LDSQ processing, namely, network traversal and object lookup, ROAD organizes a large road network as a hierarchy of interconnected regional subnetworks (called Rnets). Each Rnet is augmented with 1) shortcuts and 2) object abstracts to accelerate network traversals and …
Content Contribution In Social Media: The Case Of Youtube, Qian Tang, Bin Gu, Andrew B. Whinston
Content Contribution In Social Media: The Case Of Youtube, Qian Tang, Bin Gu, Andrew B. Whinston
Research Collection School Of Computing and Information Systems
Social media allows individuals and businesses to contribute contents for public viewing. However, little is known about the underlying incentives that why content providers derive utilities from such activities. In this study, we build a dynamic structural model to recover the utility function for content providers. Our model distinguishes short-term payoffs based on ad revenue sharing from long-term payoffs driven by content providers' reputation. The model was estimated using a panel data of 914 top 1000 video providers on You Tube from Jun 7th, 2010, to Aug 7th, 2011 since top providers are more likely to be encouraged by these …
Optimal Decision Making For Online Referral Marketing, Zhiling Guo
Optimal Decision Making For Online Referral Marketing, Zhiling Guo
Research Collection School Of Computing and Information Systems
Widely available web 2.0 technologies not only bring rich and interactive user experiences, but also easily help users advertise products or services on their own blogs and social network webpages. Online referral marketing, for example, is a business practice that rewards customers who successfully refer other customers to a website or upon completion of a sale usually via their own social contacts. The referral rewards come in different forms such as shopping vouchers, redeemable points, discounts, prizes, cash payments, etc. We develop an analytical model to evaluate the business potential of incorporating an online referral marketing program into the firm's …
Tweets And Votes: A Study Of The 2011 Singapore General Election, Marko M. Skoric, Nathaniel D. Poor, Palakorn Achananuparp, Ee Peng Lim, Jing Jiang
Tweets And Votes: A Study Of The 2011 Singapore General Election, Marko M. Skoric, Nathaniel D. Poor, Palakorn Achananuparp, Ee Peng Lim, Jing Jiang
Research Collection School Of Computing and Information Systems
This study focuses on the uses of Twitter during the elections, examining whether the messages posted online are reflective of the climate of public opinion. Using Twitter data obtained during the official campaign period of the 2011 Singapore General Election, we test the predictive power of tweets in forecasting the election results. In line with some previous studies, we find that during the elections the Twitter sphere represents a rich source of data for gauging public opinion and that the frequency of tweets mentioning names of political parties, political candidates and contested constituencies could be used to make predictions about …
Consumer-Driven Innovation Management, Arcot Desai Narasimhalu, Shekhar Mitra
Consumer-Driven Innovation Management, Arcot Desai Narasimhalu, Shekhar Mitra
Research Collection School Of Computing and Information Systems
The evolution of human society leads to increased affluence and prosperity of certain populations, sometimes at the expense of well-established markets. Market leaders in products and services tend to be so focused on their current customer base that they are caught off guard with the changes in markets created by the evolution. These changes often go unnoticed until it is too late. The change in customer base often requires the repositioning of products and services through innovations, which address new and emerging markets. Some of these changes could potentially result in tectonic market shifts that force innovation managers to involve …
A Fuzzy Logic Multi-Criteria Decision Framework For Selecting It Service Providers, Amir Karami, Zhiling Guo
A Fuzzy Logic Multi-Criteria Decision Framework For Selecting It Service Providers, Amir Karami, Zhiling Guo
Research Collection School Of Computing and Information Systems
Selecting IT service providers in information systems outsourcing involves both qualitative and quantitative evaluations. This paper proposes an integrated multi-criteria decision-making (MCDM) framework to effectively handle uncertainty and subjectivity in the vendor selection process. The proposed methods apply fuzzy logic approach to integrate qualitative survey data into traditional multi-criteria decision models such as data envelope analysis (DEA), analytical hierarchy process (AHP) methods, and TOPSIS. Based on case studies from Iranian banking industry, we empirically test the proposed framework and show it is superior to existing methods. We demonstrate that the fuzzy logic approach provides a robust analysis for vendor selection …
Value Relevance Of Blog Visibility, Nan Hu, Ling Liu, Arindam Tripathy, Lee J. Yao
Value Relevance Of Blog Visibility, Nan Hu, Ling Liu, Arindam Tripathy, Lee J. Yao
Research Collection School Of Computing and Information Systems
This study empirically examines the effect of a non-traditional information source, namely a firm's blog visibility on the capital market valuation of firms. After controlling for earnings, book value of equity and other value relevant variables, such as traditional media exposure, R&D spending, and advertising expense, we find a positive association between a firm's blog visibility and its capital market valuation. In addition, we find blog visibility Grange causes trading, not vice versa. Our findings indicate that non-traditional information sources such as blogs help disseminate information and influence consumers' investment decisions by capturing their attention.
Capir: Collaborative Action Planning With Intention Recognition, Nguyen T., Hsu D., Lee W., Tze-Yun Leong, Kaelbling L., Lozano-Perez T., Grant A.
Capir: Collaborative Action Planning With Intention Recognition, Nguyen T., Hsu D., Lee W., Tze-Yun Leong, Kaelbling L., Lozano-Perez T., Grant A.
Research Collection School Of Computing and Information Systems
We apply decision theoretic techniques to construct nonplayer characters that are able to assist a human player in collaborative games. The method is based on solving Markov decision processes, which can be difficult when the game state is described by many variables. To scale to more complex games, the method allows decomposition of a game task into subtasks, each of which can be modelled by a Markov decision process. Intention recognition is used to infer the subtask that the human is currently performing, allowing the helper to assist the human in performing the correct task. Experiments show that the method …
Retrieval-Based Face Annotation By Weak Label Regularized Local Coordinate Coding, Dayong Wang, Steven C. H. Hoi, Ying He, Jianke Zhu
Retrieval-Based Face Annotation By Weak Label Regularized Local Coordinate Coding, Dayong Wang, Steven C. H. Hoi, Ying He, Jianke Zhu
Research Collection School Of Computing and Information Systems
Retrieval-based face annotation is a promising paradigm in mining massive web facial images for automated face annotation. Such an annotation paradigm usually encounters two key challenges. The first challenge is how to efficiently retrieve a short list of most similar facial images from facial image databases, and the second challenge is how to effectively perform annotation by exploiting these similar facial images and their weak labels which are often noisy and incomplete. In this paper, we mainly focus on tackling the second challenge of the retrieval-based face annotation paradigm. In particular, we propose an effective Weak Label Regularized Local Coordinate …
Validation Of A Model Of Information Systems User Competency, Brenda Eschenbrenner, Fiona Fui-Hoon Nah
Validation Of A Model Of Information Systems User Competency, Brenda Eschenbrenner, Fiona Fui-Hoon Nah
Research Collection School Of Computing and Information Systems
IS user competency, or the ability to realize the fullest potential and the greatest performance from IS use, is important for IS users. However, which factors contribute to IS user competency is unclear. Based on the findings of previous research, a model of IS user competency was developed that focuses on IS-specific characteristics: (i) domain knowledge of and skills in IS, (ii) willingness to try and to explore IS, and (iii) capability of perceiving IS value. The model was validated using the survey approach and the findings suggest that all three factors are pivotal to IS user competency, with willingness …
An Effective Approach For Topicspecific Opinion Summarization, Binyang Li, Lanjun Zhou, Wei Gao, Kam-Fai Wong, Zhongyu Wei
An Effective Approach For Topicspecific Opinion Summarization, Binyang Li, Lanjun Zhou, Wei Gao, Kam-Fai Wong, Zhongyu Wei
Research Collection School Of Computing and Information Systems
Topic-specific opinion summarization (TOS) plays an important role in helping users digest online opinions, which targets to extract a summary of opinion expressions specified by a query, i.e. topic-specific opinionated information (TOI). A fundamental problem in TOS is how to effectively represent the TOI of an opinion so that salient opinions can be summarized to meet user’s preference. Existing approaches for TOS are either limited by the mismatch between topic-specific information and its corresponding opinionated information or lack of ability to measure opinionated information associated with different topics, which in turn affect the performance seriously. In this paper, we represent …
Gender Differences In Virtual Collaboration On A Creative Design Task, Shu Schiller, Fiona Nah, Brian Mennecke, Keng Siau
Gender Differences In Virtual Collaboration On A Creative Design Task, Shu Schiller, Fiona Nah, Brian Mennecke, Keng Siau
Research Collection School Of Computing and Information Systems
Collaboration is an important activity in every organization because it fundamentally affects work processes and organizational outcomes. Diversity adds complexity to the mechanism of virtual teams because teams routinely operate virtually by spanning temporal, geographic, national, and cultural boundaries. One important way to decode such complexity is to understand gender differences and their impacts on virtual modes of collaboration. In this research, we examine gender differences and how they influence outcomes and attitudes on virtual collaboration in the context of team gender composition. Phase one of our study involved male-male dyads and female-female dyads that collaborated virtually in Second Life. …
New Theories And Methods For Technology Adoption Research, Robert J. Kauffman, Angsana A. Techatassanasoontorn
New Theories And Methods For Technology Adoption Research, Robert J. Kauffman, Angsana A. Techatassanasoontorn
Research Collection School Of Computing and Information Systems
This special issue includes six articles on different aspects of technology adoption that represent the development and application of different theoretical and methodological approaches to the business problems that they treat. In terms of theory, three of the articles use behavioral and organizational theories, including adaptive structuration theory, management fashion theory, the unified theory of technology acceptance, the technology acceptance model, and diffusion of innovation theory. The other two are based on economic theory, including network effects theory, and economic growth theory. The methods used are also dramatically different in each of the studies. Three studies use field research and …
Context-Based Friend Suggestion In Online Photo-Sharing Community, Ting Yao, Chong-Wah Ngo, Tao Mei
Context-Based Friend Suggestion In Online Photo-Sharing Community, Ting Yao, Chong-Wah Ngo, Tao Mei
Research Collection School Of Computing and Information Systems
With the popularity of social media, web users tend to spend more time than before for sharing their experience and interest in online photo-sharing sites. The wide variety of sharing behaviors generate different metadata which pose new opportunities for the discovery of communities. We propose a new approach, named context-based friend suggestion, to leverage the diverse form of contextual cues for more effective friend suggestion in the social media community. Different from existing approaches, we consider both visual and geographical cues, and develop two user-based similarity measurements, i.e., visual similarity and geo similarity for characterizing user relationship. The problem of …
Cross Media Hyperlinking For Search Topic Browsing, Song Tan, Chong-Wah Ngo, Hung-Khoon Tan, Lei Pang
Cross Media Hyperlinking For Search Topic Browsing, Song Tan, Chong-Wah Ngo, Hung-Khoon Tan, Lei Pang
Research Collection School Of Computing and Information Systems
With the rapid growth of social media, there are plenty of information sources freely available online for use. Nevertheless, how to synchronize and leverage these diverse forms of information for multimedia applications remains a problem yet to be seriously studied. This paper investigates the synchronization of multiple media content in the physical form of hyperlinking them. The ultimate goal is to develop browsing systems that author search results with rich media information mined from various knowledge sources. The authoring enables the vivid visualization and exploration of different information landscapes inherent in search results. Several key techniques are studied in this …