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Articles 2281 - 2310 of 3560

Full-Text Articles in Databases and Information Systems

On Modeling Brand Preferences In Item Adoptions, Minh Duc Luu, Ee Peng Lim, Freddy Chong-Tat Chua Jun 2014

On Modeling Brand Preferences In Item Adoptions, Minh Duc Luu, Ee Peng Lim, Freddy Chong-Tat Chua

Research Collection School Of Computing and Information Systems

In marketing and advertising, developing and managingbrands value represent the core activities performedby companies. Successful brands attract buyers andadopters, which in turn increase the companies’ value.Given a set of user-item adoption data, can we inferbrand effects from users adopting items? To answerthis question, we develop the Brand Item Topic Model(BITM) that incorporates users’ brand preferences inthe process of item adoption by the users. We evaluateour model using synthetic and two real world datasetsagainst baseline models which do not consider brand effects.The results show that BITM can determine userswho demonstrate brand preferences and predict itemadoptions more accurately.

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Hydra: Large-Scale Social Identity Linkage Via Heterogeneous Behavior Modeling, Siyuan Liu, Shuhui Wang, Feida Zhu, Jinbo Zhang, Ramayya Krishnan Jun 2014

Hydra: Large-Scale Social Identity Linkage Via Heterogeneous Behavior Modeling, Siyuan Liu, Shuhui Wang, Feida Zhu, Jinbo Zhang, Ramayya Krishnan

Research Collection School Of Computing and Information Systems

We study the problem of large-scale social identity linkage across different social media platforms, which is of critical importance to business intelligence by gaining from social data a deeper understanding and more accurate profiling of users. This paper proposes HYDRA, a solution framework which consists of three key steps: (I) modeling heterogeneous behavior by long-term behavior distribution analysis and multi-resolution temporal information matching; (II) constructing structural consistency graph to measure the high-order structure consistency on users' core social structures across different platforms; and (III) learning the mapping function by multi-objective optimization composed of both the supervised learning on pair-wise ID …

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Online Community Transition Detection, Biying Tan, Feida Zhu, Qiang Qu, Siyuan Liu Jun 2014

Online Community Transition Detection, Biying Tan, Feida Zhu, Qiang Qu, Siyuan Liu

Research Collection School Of Computing and Information Systems

Mining user behavior patterns in social networks is of great importance in user behavior analysis, targeted marketing, churn prediction and other applications. However, less effort has been made to study the evolution of user behavior in social communities. In particular, users join and leave communities over time. How to automatically detect the online community transitions of individual users is a research problem of immense practical value yet with great technical challenges. In this paper, we propose an algorithm based on the Minimum Description Length (MDL) principle to trace the evolution of community transition of individual users, adaptive to the noisy …

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Flow In Gaming: Literature Synthesis And Framework Development, Fiona Fui-Hoon Nah, B. Eschenbrenner, Q. Zeng, V. Telaprolu, S. Sepehr Jun 2014

Flow In Gaming: Literature Synthesis And Framework Development, Fiona Fui-Hoon Nah, B. Eschenbrenner, Q. Zeng, V. Telaprolu, S. Sepehr

Research Collection School Of Computing and Information Systems

Flow, a state of optimal experience where one is completely absorbed and immersed in an activity, is an important phenomenon for studying and designing games. In this article, we synthesise the literature on flow in gaming to discern existing research streams, and identify the antecedents, dimensions, and outcomes of flow which are then integrated into a framework. Based on the findings, we provide suggestions for game design elements that practitioners, such as game designers, may find useful for creating or inducing flow in gaming. We also discuss implications for research and practice as well as provide suggestions for future research.

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Information Systems User Competency: A Conceptual Foundation, B. Eschenbrenner, Fiona Fui-Hoon Nah Jun 2014

Information Systems User Competency: A Conceptual Foundation, B. Eschenbrenner, Fiona Fui-Hoon Nah

Research Collection School Of Computing and Information Systems

Research has identified a variety of factors that influence people’s intentions to use IS and their degree of IS use. However, what has not been well understood are the characteristics of competent IS users who are proficient in using IS and are able to achieve quality IS usage. Considering that improving IS users’ abilities to more efficiently and effectively use IS has always been and remains a challenge, research that provides a comprehensive view of the characteristics associated with competent IS users is warranted. This paper addresses this research question by proposing a conceptual foundation for IS user competency. Based …

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Institutional Boundaries And Trust Of Virtual Teams In Collaborative Design: An Experimental Study In A Virtual World Environment, Shu Z. Schiller, Brian Mennecke, Fiona Fui-Hoon Nah, Andy Luse Jun 2014

Institutional Boundaries And Trust Of Virtual Teams In Collaborative Design: An Experimental Study In A Virtual World Environment, Shu Z. Schiller, Brian Mennecke, Fiona Fui-Hoon Nah, Andy Luse

Research Collection School Of Computing and Information Systems

Members of virtual teams often collaborate within and across institutional boundaries. This research investigates the effects of boundary spanning conditions on the development of team trust and team satisfaction. Two hundred and eighty-two participants carried out a collaborative design task over several weeks in a virtual world, Second Life. Multigroup structural equation modeling was used to examine our research model, which compares individual level measurement between two boundary spanning team conditions. The results indicate that trusting beliefs have a positive impact on team trust, which in turn, influences team satisfaction. Further, we found that, compared to cross-boundary teams, within-boundary teams …

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Gamification Of Education: A Review Of Literature, Fiona Fui-Hoon Nah, Qing Zeng, Venkata R. Telaprolu, Abhishek Padmanabhuni Ayyappa, Brenda Eschenbrenner Jun 2014

Gamification Of Education: A Review Of Literature, Fiona Fui-Hoon Nah, Qing Zeng, Venkata R. Telaprolu, Abhishek Padmanabhuni Ayyappa, Brenda Eschenbrenner

Research Collection School Of Computing and Information Systems

We synthesized the literature on gamification of education by conducting a review of the literature on gamification in the educational and learning context. Based on our review, we identified several game design elements that are used in education. These game design elements include points, levels/stages, badges, leaderboards, prizes, progress bars, storyline, and feedback. We provided examples from the literature to illustrate the application of gamification in the educational context.

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Joint Virtual Machine And Bandwidth Allocation In Software Defined Network (Sdn) And Cloud Computing Environments, Jonathan David Chase, Rakpong Kaewpuang, Wen Yonggang, Dusit Niyato Jun 2014

Joint Virtual Machine And Bandwidth Allocation In Software Defined Network (Sdn) And Cloud Computing Environments, Jonathan David Chase, Rakpong Kaewpuang, Wen Yonggang, Dusit Niyato

Research Collection School Of Computing and Information Systems

Cloud computing provides users with great flexibility when provisioning resources, with cloud providers offering a choice of reservation and on-demand purchasing options. Reservation plans offer cheaper prices, but must be chosen in advance, and therefore must be appropriate to users' requirements. If demand is uncertain, the reservation plan may not be sufficient and on-demand resources have to be provisioned. Previous work focused on optimally placing virtual machines with cloud providers to minimize total cost. However, many applications require large amounts of network bandwidth. Therefore, considering only virtual machines offers an incomplete view of the system. Exploiting recent developments in software …

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An Air Index For Spatial Query Processing In Road Networks, Weiwei Sun, Chunan Chen, Baihua Zheng, Chong Chen, Peng Liu Jun 2014

An Air Index For Spatial Query Processing In Road Networks, Weiwei Sun, Chunan Chen, Baihua Zheng, Chong Chen, Peng Liu

Research Collection School Of Computing and Information Systems

Spatial queries such as range query and kNN query in road networks have received a growing number of attention in real life. Considering the large population of the users and the high overhead of network distance computation, it is extremely important to guarantee the efficiency and scalability of query processing. Motivated by the scalable and secure properties of wireless broadcast model, this paper presents an air index called Network Partition Index (NPI) to support efficient spatial query processing in road networks via wireless broadcast. The main idea is to partition the road network into a number of regions and then …

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On Coordinating Pervasive Persuasive Agents, Budhitama Subagdja, Ah-Hwee Tan May 2014

On Coordinating Pervasive Persuasive Agents, Budhitama Subagdja, Ah-Hwee Tan

Research Collection School Of Computing and Information Systems

There is a growing interest in applying multiagent systems for smart-home environment supporting self-caring elderly. In this paper we investigate situations and conditions for coordination for such kind of system. We specify a high level architecture of it based on the notions of beliefs, desires, and intentions for both individual and group behavior of the agents including the human occupant's. The framework enables flexible coordinations among loosely-coupled heterogeneous agents that converse with the user. This work is conducted towards producing a coordination framework for agents and people in such a kind of smart-home environment as mentioned.

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Declarative-Procedural Memory Interaction In Learning Agents, Wenwen Wang, Ah-Hwee Tan, Loo-Nin Teow, Tan Yuan-Sin May 2014

Declarative-Procedural Memory Interaction In Learning Agents, Wenwen Wang, Ah-Hwee Tan, Loo-Nin Teow, Tan Yuan-Sin

Research Collection School Of Computing and Information Systems

It has been well recognized that human makes use of both declarative memory and procedural memory for decision making and problem solving. In this paper, we propose a computational model with the overall architecture and individual processes for realizing the interaction between the declarative and procedural memory based on self-organizing neural networks. We formalize two major types of memory interactions and show how each of them can be embedded into autonomous reinforcement learning agents. Our experiments based on the Toad and Frog puzzle and a strategic game known as Starcraft Broodwar have shown that the cooperative interaction between declarative knowledge …

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Simple Effective Named Entity Recognition For Microblogs: Arabic As An Example, Kareem Darwish, Wei Gao May 2014

Simple Effective Named Entity Recognition For Microblogs: Arabic As An Example, Kareem Darwish, Wei Gao

Research Collection School Of Computing and Information Systems

No abstract provided.

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Haptics In Remote Collaborative Exercise Systems For Seniors, Hesam Alizadeh, Richard Tang, Ehud Sharlin, Anthony Tang May 2014

Haptics In Remote Collaborative Exercise Systems For Seniors, Hesam Alizadeh, Richard Tang, Ehud Sharlin, Anthony Tang

Research Collection School Of Computing and Information Systems

Group exercise provides motivation to follow and maintain a healthy daily exercise schedule while enjoying beneficial encouragement and social support from friends and exercise partners. However, mobility and transportation issues frequently prevent seniors from engaging in group activities. To address this problem, we investigated the exercise needs of seniors and developed a prototype remote exercise system. Our system uses haptic feedback to simulate assistive pushing and pulling of limbs when exercising with a partner. We developed three distinct vibration metaphors -- constant push/pull, corrective feedback, and notification -- to convey engagement and connection between exercise partners. We conducted a preliminary …

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Shopprofiler: Profiling Shops With Crowdsourcing Data, Xiaonan Guo, Eddie C. L. Chan, Ce Liu, Kaishun Wu, Siyuan Liu, Lionel Ni May 2014

Shopprofiler: Profiling Shops With Crowdsourcing Data, Xiaonan Guo, Eddie C. L. Chan, Ce Liu, Kaishun Wu, Siyuan Liu, Lionel Ni

Research Collection School Of Computing and Information Systems

Sensing data from mobile phones provide us exciting and profitable applications. Recent research focuses on sensing indoor environment, but suffers from inaccuracy because of the limited reachability of human traces or requires human intervention to perform sophisticated tasks. In this paper, we present ShopProfiler, a shop profiling system on crowdsourcing data. First, we extract customer movement patterns from traces. Second, we improve accuracy of building floor plan by adopting a gradient-based approach and then localize shops through WiFi heat map. Third, we categorize shops by designing an SVM classifier in shop space to support multi-label classification. Finally, we infer brand …

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Visual Analysis Of Uncertainty In Trajectories, Lu Lu, Nan Cao, Siyuan Liu, Lionel Ni, Xiaoru Yuan, Huamin Qu May 2014

Visual Analysis Of Uncertainty In Trajectories, Lu Lu, Nan Cao, Siyuan Liu, Lionel Ni, Xiaoru Yuan, Huamin Qu

Research Collection School Of Computing and Information Systems

Mining trajectory datasets has many important applications. Real trajectory data often involve uncertainty due to inadequate sampling rates and measurement errors. For some trajectories, their precise positions cannot be recovered and the exact routes that vehicles traveled cannot be accurately reconstructed. In this paper, we investigate the uncertainty problem in trajectory data and present a visual analytics system to reveal, analyze, and solve the uncertainties associated with trajectory samples. We first propose two novel visual encoding schemes called the road map analyzer and the uncertainty lens for discovering road map errors and visually analyzing the uncertainty in trajectory data respectively. …

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Detecting Anomaly Collections Using Extreme Feature Ranks, Hanbo Dai, Feida Zhu, Ee Peng Lim, Hwee Hwa Pang May 2014

Detecting Anomaly Collections Using Extreme Feature Ranks, Hanbo Dai, Feida Zhu, Ee Peng Lim, Hwee Hwa Pang

Research Collection School Of Computing and Information Systems

Detecting anomaly collections is an important task with many applications, including spam and fraud detection. In an anomaly collection, entities often operate in collusion and hold different agendas to normal entities. As a result, they usually manifest collective extreme traits, i.e., members of an anomaly collection are consistently clustered toward the top or bottom ranks on certain features. We therefore propose to detect these anomaly collections by extreme feature ranks. We introduce a novel anomaly definition called Extreme Rank Anomalous Collection or ERAC. We propose a new measure of anomalousness capturing collective extreme traits based on a statistical model. As …

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An Integrated Model For User Attribute Discovery: A Case Study On Political Affiliation Identification, Swapna Gottipati, Minghui Qiu, Liu Yang, Feida Zhu, Jing Jiang May 2014

An Integrated Model For User Attribute Discovery: A Case Study On Political Affiliation Identification, Swapna Gottipati, Minghui Qiu, Liu Yang, Feida Zhu, Jing Jiang

Research Collection School Of Computing and Information Systems

Discovering user demographic attributes from social media is a problem of considerable interest. The problem setting can be generalized to include three components — users, topics and behaviors. In recent studies on this problem, however, the behavior between users and topics are not effectively incorporated. In our work, we proposed an integrated unsupervised model which takes into consideration all the three components integral to the task. Furthermore, our model incorporates collaborative filtering with probabilistic matrix factorization to solve the data sparsity problem, a computational challenge common to all such tasks. We evaluated our method on a case study of user …

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Handling Location Uncertainty In Event Driven Experimentation, Kartik Muralidharan, Srinivasan Seshan, Narayan Ramasubbu, Rajesh Krishna Balan May 2014

Handling Location Uncertainty In Event Driven Experimentation, Kartik Muralidharan, Srinivasan Seshan, Narayan Ramasubbu, Rajesh Krishna Balan

Research Collection School Of Computing and Information Systems

The wide spread use of smart phones has ushered in a wave of context-based advertising services that operate on pre-defined user events. A prime example is Location Based Advertising. What is missing though, is the ability to experiment with these services under varying event conditions with real users using their regular phones in real-world environments. Such experiments provide greater insight into user needs for and responsiveness towards context-based advertising applications. However, these event-driven experiments rely on data that arrive from sources such as mobile sensors which have inherent uncertainties associated with them. This effects the interpretation of the outcome of …

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Celebrowser: An Example Of Browsing Big Data On Small Device, Song Tan, Chong-Wah Ngo, Jun Xu, Yong Rui Apr 2014

Celebrowser: An Example Of Browsing Big Data On Small Device, Song Tan, Chong-Wah Ngo, Jun Xu, Yong Rui

Research Collection School Of Computing and Information Systems

In this demonstration, we demonstrate a mobile-based celebrity video browsing system called CeleBrowser. Using this system, users can interactively switch among four views: people-centric, timeline-centric, month-centric and topic-centric, for browsing celebrity-related hot videos. A peculiarity of the demonstration is to highlight the advantage of multiperspective information organization and presentation in engaging users for exploratory browsing of large number of Web videos on a device with small screen. Technology-wise the demonstration shows how query logs collected for six months from two vertical search engines are leveraged for mining hot events and videos of celebrities.

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Community Discovery In Social Networks Via Heterogeneous Link Association And Fusion, Lei Meng, Ah-Hwee Tan Apr 2014

Community Discovery In Social Networks Via Heterogeneous Link Association And Fusion, Lei Meng, Ah-Hwee Tan

Research Collection School Of Computing and Information Systems

Discovering social communities of web users through clustering analysis of heterogeneous link associations has drawn much attention. However, existing approaches typically require the number of clusters a prior, do not address the weighting problem for fusing heterogeneous types of links and have a heavy computational cost. In this paper, we explore the feasibility of a newly proposed heterogeneous data clustering algorithm, called Generalized Heterogeneous Fusion Adaptive Resonance Theory (GHF-ART), for discovering communities in heterogeneous social networks. Different from existing algorithms, GHF-ART performs real-time matching of patterns and one-pass learning which guarantee its low computational cost. With a vigilance parameter to …

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Online Multi-Modal Distance Metric Learning With Application To Image Retrieval, Pengcheng Wu, Steven C. H. Hoi, Peilin Zhao, Chunyan Miao, Zhi-Yong Liu Apr 2014

Online Multi-Modal Distance Metric Learning With Application To Image Retrieval, Pengcheng Wu, Steven C. H. Hoi, Peilin Zhao, Chunyan Miao, Zhi-Yong Liu

Research Collection School Of Computing and Information Systems

See https://ink.library.smu.edu.sg/sis_research/2924/. Distance metric learning (DML) is an important technique to improve similarity search in content-based image retrieval. Despite being studied extensively, most existing DML approaches typically adopt a single-modal learning framework that learns the distance metric on either a single feature type or a combined feature space where multiple types of features are simply concatenated. Such single-modal DML methods suffer from some critical limitations: (i) some type of features may significantly dominate the others in the DML task due to diverse feature representations; and (ii) learning a distance metric on the combined high-dimensional feature space can be extremely …

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Cimloc: A Crowdsourcing Indoor Digital Map Construction System For Localization, Xiuming Zhang, Yunye Jin, Hwee Xian Tan, Wee-Seng Soh Apr 2014

Cimloc: A Crowdsourcing Indoor Digital Map Construction System For Localization, Xiuming Zhang, Yunye Jin, Hwee Xian Tan, Wee-Seng Soh

Research Collection School Of Computing and Information Systems

Indoor maps, as crucial prerequisites for many indoor localization and navigation systems, are sometimes inaccessible. The absence of an indoor map database and the high cost of manually constructing an indoor map produce a need for an inexpensive and efficient way to dynamically construct indoor maps. The ubiquity of sensor-equipped mobile devices enables us to crowdsource user trajectories, out of which indoor digital maps can be automatically constructed at low costs. Similar to other crowdsourced data, the collected user trajectories are often noisy and of low fidelity, which poses a challenge to the accurate map construction. To alleviate this problem, …

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On Modeling Community Behaviors And Sentiments In Microblogging, Tuan Anh Hoang, William Cohen, Ee Peng Lim Apr 2014

On Modeling Community Behaviors And Sentiments In Microblogging, Tuan Anh Hoang, William Cohen, Ee Peng Lim

Research Collection School Of Computing and Information Systems

In this paper, we propose the CBS topic model, a probabilistic graphical model, to derive the user communities in microblogging networks based on the sentiments they express on their generated content and behaviors they adopt. As a topic model, CBS can uncover hidden topics and derive user topic distribution. In addition, our model associates topic-specific sentiments and behaviors with each user community. Notably, CBS has a general framework that accommodates multiple types of behaviors simultaneously. Our experiments on two Twitter datasets show that the CBS model can effectively mine the representative behaviors and emotional topics for each community. We also …

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Latent Factor Transition For Dynamic Collaborative Filtering, Chengyi Zhang, Ke Wang, Hongkun Yu, Jianling Sun, Ee Peng Lim Apr 2014

Latent Factor Transition For Dynamic Collaborative Filtering, Chengyi Zhang, Ke Wang, Hongkun Yu, Jianling Sun, Ee Peng Lim

Research Collection School Of Computing and Information Systems

No abstract provided.

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On Finding The Point Where There Is No Return: Turning Point Mining On Game Data, Wei Gong, Ee Peng Lim, Feida Zhu, Achananuparp Palakorn, David Lo Apr 2014

On Finding The Point Where There Is No Return: Turning Point Mining On Game Data, Wei Gong, Ee Peng Lim, Feida Zhu, Achananuparp Palakorn, David Lo

Research Collection School Of Computing and Information Systems

Gaming expertise is usually accumulated through playing or watching many game instances, and identifying critical moments in these game instances called turning points. Turning point rules (shorten as TPRs) are game patterns that almost always lead to some irreversible outcomes. In this paper, we formulate the notion of irreversible outcome property which can be combined with pattern mining so as to automatically extract TPRs from any given game datasets. We specifically extend the well-known PrefixSpan sequence mining algorithm by incorporating the irreversible outcome property. To show the usefulness of TPRs, we apply them to Tetris, a popular game. We mine …

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Modeling Contextual Agreement In Preferences, Ha Loc Do, Hady Wirawan Lauw Apr 2014

Modeling Contextual Agreement In Preferences, Ha Loc Do, Hady Wirawan Lauw

Research Collection School Of Computing and Information Systems

Personalization, or customizing the experience of each individual user, is seen as a useful way to navigate the huge variety of choices on the Web today. A key tenet of personalization is the capacity to model user preferences. The paradigm has shifted from that of individual preferences, whereby we look at a user's past activities alone, to that of shared preferences, whereby we model the similarities in preferences between pairs of users (e.g., friends, people with similar interests). However, shared preferences are still too granular, because it assumes that a pair of users would share preferences across all items. We …

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Recurrent Chinese Restaurant Process With A Duration-Based Discount For Event Identification From Twitter, Qiming Diao, Jing Jiang Apr 2014

Recurrent Chinese Restaurant Process With A Duration-Based Discount For Event Identification From Twitter, Qiming Diao, Jing Jiang

Research Collection School Of Computing and Information Systems

Due to the fast development of social media on the Web, Twitter has become one of the major platforms for people to express themselves. Because of the wide adoption of Twitter, events like breaking news and release of popular videos can easily catch people’s attention and spread rapidly on Twitter, and the number of relevant tweets approximately reflects the impact of an event. Event identification and analysis on Twitter has thus become an important task. Recently the Recurrent Chinese Restaurant Process (RCRP) has been successfully used for event identification from news streams and news-centric social media streams. However, these models …

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Laser: A Living Analytics Experimentation System For Large-Scale Online Controlled Experiments, Kwan-Hui Lim, Ee Peng Lim, Achananuparp Palakorn, Adrian Vu, Agus Trisnajaya Kwee, Feida Zhu Apr 2014

Laser: A Living Analytics Experimentation System For Large-Scale Online Controlled Experiments, Kwan-Hui Lim, Ee Peng Lim, Achananuparp Palakorn, Adrian Vu, Agus Trisnajaya Kwee, Feida Zhu

Research Collection School Of Computing and Information Systems

Tracking user browsing data and measuring the effectiveness of website design and web services are important to businesses that want to attract the consumers today who spend much more time online than before. Instead of using randomized controlled experiments, the existing approach simply tracks user browsing behaviors before and after a change is made to website design or web services, and evaluate the differences. To address the effects caused by hidden factors (e.g. promotion activities on the website) and to give fair comparison of different website designs, we propose the LASER system, a unified experimentation platform that enables randomized online …

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Do You Know The Speaker?: An Online Experiment With Authority Messages On Event Websites, Kwan-Hui Lim, Binyan Jiang, Ee Peng Lim, Achananuparp Palakorn Apr 2014

Do You Know The Speaker?: An Online Experiment With Authority Messages On Event Websites, Kwan-Hui Lim, Binyan Jiang, Ee Peng Lim, Achananuparp Palakorn

Research Collection School Of Computing and Information Systems

With the widespread adoption of the Web, many companies and organizations have established websites that provide information and support online transactions (e.g., buying products or viewing content). Unfortunately, users have limited attention to spare for interacting with online sites. Hence, it is of utmost importance to design sites that attract user attention and effectively guide users to the product or content items they like. Thus, we propose a novel and scalable experimentation approach to evaluate the effectiveness of online site designs. Our case study focuses on the effects of an authority message on visitors' browsing behavior on workshop and seminar …

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Adoption Of Mobile Information Services: An Empirical Study, S. Gao, J. Krogstie, Keng Siau Apr 2014

Adoption Of Mobile Information Services: An Empirical Study, S. Gao, J. Krogstie, Keng Siau

Research Collection School Of Computing and Information Systems

This study investigates the adoption of mobile information services at a Norwegian university. By expanding the Technology Acceptance Model (TAM), a new research model, known as the mobile services acceptance model (MSAM), is proposed. Based on the research model, seven research hypotheses are presented. The proposed research model and research hypotheses were empirically tested using data collected from a survey of users of a mobile service, extended Mobile Student Information Systems (eMSIS), at a Norwegian university. The findings indicate that the fitness of the research model is good. Support was also found for the seven research hypotheses. Among the factors, …

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