Open Access. Powered by Scholars. Published by Universities.®

Digital Commons Network™

Open Access. Powered by Scholars. Published by Universities.®

Singapore Management University

Discipline
Keyword
Publication Year
Publication
Publication Type
File Type

Articles 7771 - 7800 of 10509

Full-Text Articles in Entire DC Network

Seller Diversity On A Technology-Based Platform, Ruhai Wu, Mei Lin Jan 2013

Seller Diversity On A Technology-Based Platform, Ruhai Wu, Mei Lin

Research Collection School Of Computing and Information Systems

Managing a technology portfolio is one of the great challenges for sustained success, especially in high-technology industrieswhere technologies can be a major selling point. For engineers, this portfolio is more of a toolbox for solving design problems,but in large organizations there can be so many technologies used in different business areas that even the engineers may not beaware of all of them. When the same technologies are used in different types of products, knowledge about them can also begenerated by various groups within an organization. To improve the usefulness of a company's technology base, this paperproposes the use of a …


State Space Reduction For Sensor Networks Using Two-Level Partial Order Reduction, Manchun Zheng, David Sanán, Jun Sun, Yang Liu, Jin Song Dong, Yu Gu Jan 2013

State Space Reduction For Sensor Networks Using Two-Level Partial Order Reduction, Manchun Zheng, David Sanán, Jun Sun, Yang Liu, Jin Song Dong, Yu Gu

Research Collection School Of Computing and Information Systems

Wireless sensor networks may be used to conduct critical tasks like fire detection or surveillance monitoring. It is thus important to guarantee the correctness of such systems by systematically analyzing their behaviors. Formal verification of wireless sensor networks is an extremely challenging task as the state space of sensor networks is huge, e.g., due to interleaving of sensors and intra-sensor interrupts. In this work, we develop a method to reduce the state space significantly so that state space exploration methods can be applied to a much smaller state space without missing a counterexample. Our method explores the nature of networked …


How Strong Are The Effects Of Technological Disruption? Smartphones' Impacts On Internet And Cable Tv Services Consumption, M. R. Chang, Robert J. Kauffman, K.S. Kim Jan 2013

How Strong Are The Effects Of Technological Disruption? Smartphones' Impacts On Internet And Cable Tv Services Consumption, M. R. Chang, Robert J. Kauffman, K.S. Kim

Research Collection School Of Computing and Information Systems

Emerging technologies have created disruptions in organizational, business process and industry contexts. They act as shocks to a system. We focus on a retail telecom service provider’s offerings of different bun-dles, including mobile phones, Internet and cable TV services. We conduct empirical regularities analysis for Singapore, which was affected by the emergence of smartphones in 2009. We assess the impacts on the service bundle choices of a provider’s customers. We analyze customer switching among service bundles involving three services. We compute switching proba-bilities for each of the service levels offered, as well as between bundles. We use Markov chain transition …


Towards Next-Generation Multimedia Recommendation Systems, Jialie Shen, Shuicheng Yan, Xian-Sheng Hua Jan 2013

Towards Next-Generation Multimedia Recommendation Systems, Jialie Shen, Shuicheng Yan, Xian-Sheng Hua

Research Collection School Of Computing and Information Systems

Empowered by advances in information technology, such as social media network, digital library and mobile computing, there emerges an ever-increasing amounts of multimedia data. As the key technology to address the problem of information overload, multimedia recommendation system has been received a lot of attentions from both industry and academia. This course aims to 1) provide a series of detailed review of state-of-the-art in multimedia recommendation; 2) analyze key technical challenges in developing and evaluating next generation multimedia recommendation systems from different perspectives and 3) give some predictions about the road lies ahead of us.


Towards Efficient Sparse Coding For Scalable Image Annotation, Junshi Huang, Hairong Liu, Jialie Shen, Shuicheng Yan Jan 2013

Towards Efficient Sparse Coding For Scalable Image Annotation, Junshi Huang, Hairong Liu, Jialie Shen, Shuicheng Yan

Research Collection School Of Computing and Information Systems

Nowadays, content-based retrieval methods are still the development trend of the traditional retrieval systems. Image labels, as one of the most popular approaches for the semantic representation of images, can fully capture the representative information of images. To achieve the high performance of retrieval systems, the precise annotation for images becomes inevitable. However, as the massive number of images in the Internet, one cannot annotate all the images without a scalable and flexible (i.e., training-free) annotation method. In this paper, we particularly investigate the problem of accelerating sparse coding based scalable image annotation, whose off-the-shelf solvers are generally inefficient on …


Hypergraph Index: An Index For Context-Aware Nearest Neighbor Query On Social Networks, Yazhe Wang, Baihua Zheng Jan 2013

Hypergraph Index: An Index For Context-Aware Nearest Neighbor Query On Social Networks, Yazhe Wang, Baihua Zheng

Research Collection School Of Computing and Information Systems

Social network has been touted as the No. 2 innovation in a recent IEEE Spectrum Special Report on “Top 11 Technologies of the Decade”, and it has cemented its status as a bona fide Internet phenomenon. With more and more people starting using social networks to share ideas, activities, events, and interests with other members within the network, social networks contain a huge amount of content. However, it might not be easy to navigate social networks to find specific information. In this paper, we define a new type of queries, namely context-aware nearest neighbor (CANN) search over social network to …


Regret Based Robust Solutions For Uncertain Markov Decision Processes, Asrar Ahmed, Pradeep Reddy Varakantham, Yossiri Adulyasak, Patrick Jaillet Jan 2013

Regret Based Robust Solutions For Uncertain Markov Decision Processes, Asrar Ahmed, Pradeep Reddy Varakantham, Yossiri Adulyasak, Patrick Jaillet

Research Collection School Of Computing and Information Systems

In this paper, we seek robust policies for uncertain Markov Decision Processes (MDPs). Most robust optimization approaches for these problems have focussed on the computation of maximin policies which maximize the value corresponding to the worst realization of the uncertainty. Recent work has proposed minimax regret as a suitable alternative to the maximin objective for robust optimization. However, existing algorithms for handling minimax regret are restricted to models with uncertainty over rewards only. We provide algorithms that employ sampling to improve across multiple dimensions: (a) Handle uncertainties over both transition and reward models; (b) Dependence of model uncertainties across state, …


Engagingness And Responsiveness Behavior Models On The Enron Email Network And Its Application To Email Reply Order Prediction, Byung-Won On, Ee Peng Lim, Jing Jiang, Loo Nin Teow Jan 2013

Engagingness And Responsiveness Behavior Models On The Enron Email Network And Its Application To Email Reply Order Prediction, Byung-Won On, Ee Peng Lim, Jing Jiang, Loo Nin Teow

Research Collection School Of Computing and Information Systems

In email networks, user behaviors affect the way emails are sent and replied. While knowing these user behaviors can help to create more intelligent email services, there has not been much research into mining these behaviors. In this paper, we investigate user engagingness and responsiveness as two interaction behaviors that give us useful insights into how users email one another. Engaging users are those who can effectively solicit responses from other users. Responsive users are those who are willing to respond to other users. By modeling such behaviors, we are able to mine them and to identify engaging or responsive …


Valuation Of Participation In Social Gaming, Kwansoo Kim, Byungjoon Yoo, Robert J. Kauffman Jan 2013

Valuation Of Participation In Social Gaming, Kwansoo Kim, Byungjoon Yoo, Robert J. Kauffman

Research Collection School Of Computing and Information Systems

This study examines the value of the time that a user spends to participate in a social game. We focus on how a massive multiplayer online role-playing game (MMORPG) vendor can establish prices to encourage participation and retain its players. We estimate value through an application of the hedonic pricing model and analyze a data set for an MMORPG in Korea. The results permit us to estimate the value of game-playing time in monetary terms. Based on our empirical results, we propose an economic model and conduct numerical simulation to show how a game vendor can apply differential pricing in …


Cqarank: Jointly Model Topics And Expertise In Community Question Answering, Liu Yang, Minghui Qiu, Swapna Gottopati, Feida Zhu, Jing Jiang, Huiping Sun, Zhong Chen Jan 2013

Cqarank: Jointly Model Topics And Expertise In Community Question Answering, Liu Yang, Minghui Qiu, Swapna Gottopati, Feida Zhu, Jing Jiang, Huiping Sun, Zhong Chen

Research Collection School Of Computing and Information Systems

Community Question Answering (CQA) websites, where people share expertise on open platforms, have become large repositories of valuable knowledge. To bring the best value out of these knowledge repositories, it is critically important for CQA services to know how to find the right experts, retrieve archived similar questions and recommend best answers to new questions. To tackle this cluster of closely related problems in a principled approach, we proposed Topic Expertise Model (TEM), a novel probabilistic generative model with GMM hybrid, to jointly model topics and expertise by integrating textual content model and link structure analysis. Based on TEM results, …


Sensor Feature Selection And Combination For Stress Identification Using Combinatorial Fusion, Yong Deng, Zhonghai Wu, Chao-Hsien Chu, Qixun Zhang, D. Frank Hsu Jan 2013

Sensor Feature Selection And Combination For Stress Identification Using Combinatorial Fusion, Yong Deng, Zhonghai Wu, Chao-Hsien Chu, Qixun Zhang, D. Frank Hsu

Research Collection School Of Computing and Information Systems

The identification of stressfulness under certain driving condition is an important issue for safety, security and health. Sensors and systems have been placed or implemented as wearable devices for drivers. Features are extracted from the data collected and combined to predict symptoms. The challenge is to select the feature set most relevant for stress. In this paper, we propose a feature selection method based on the performance and the diversity between two features. The feature sets selected are then combined using a combinatorial fusion. We also compare our results with other combination methods such as naïve Bayes, support vector machine, …


Business School Evolution: Media Insights And The Future Outlook, Gillian Goh, Michelle P. Lee, Howard Thomas Jan 2013

Business School Evolution: Media Insights And The Future Outlook, Gillian Goh, Michelle P. Lee, Howard Thomas

Research Collection Lee Kong Chian School Of Business

Over the last two decades business schools and management education have received much attention in the media – witnessed by the boom in media rankings and the myriad topics discussed. Global events, such as the global financial crisis, have often been the precipitator of intense scrutiny of management education and calls for its reform.


Symbolic Model-Checking Of Stateful Timed Csp Using Bdd And Digitization, Truong Khanh Nguyen, Jun Sun, Yang Liu, Jin Song Dong Dec 2012

Symbolic Model-Checking Of Stateful Timed Csp Using Bdd And Digitization, Truong Khanh Nguyen, Jun Sun, Yang Liu, Jin Song Dong

Research Collection School Of Computing and Information Systems

Stateful Timed CSP has been recently proposed to model (and verify) hierarchical real-time systems. It is an expressive modeling language which combines data structure/operations, complicated control flows (modeled using compositional process operators adopted from Timed CSP), and real-time requirements like deadline and within. It has been shown that Stateful Timed CSP is equivalent to closed timed automata with silent transitions, which implies that the timing constraints of Stateful Timed CSP can be captured using explicit tick events, through digitization. In order to tackle the state space explosion problem, we develop a BDD-based symbolic model checking approach to verify Stateful Timed …


Designing Selection Systems For Medicine: The Importance Of Balancing Predictive And Political Validity In High-Stakes Selection Contexts, Fiona Patterson, Filip Lievens, Máire Kerrin, Lara Zibarras, Bernd Carette Dec 2012

Designing Selection Systems For Medicine: The Importance Of Balancing Predictive And Political Validity In High-Stakes Selection Contexts, Fiona Patterson, Filip Lievens, Máire Kerrin, Lara Zibarras, Bernd Carette

Research Collection Lee Kong Chian School Of Business

Selection into medical education and training is a high-stakes process. A key unanswered issue is the effectiveness of measuring noncognitive predictors via both low-fidelity and high-fidelity selection approaches in this high-stakes context. We review studies investigating the effectiveness of multiple selection instruments in terms of predictive validity, incremental validity, and applicant reactions in both entry-level and advanced-level medical selection. Our results show that the situational judgment test (SJT) is the best single predictor of performance, operationalized in multiple ways. In addition, the low-fidelity SJT has incremental predictive power over cognitively oriented tests, and high-fidelity assessment center (AC) exercises add incremental …


The Impact Of Macro Socio-Economic Drivers And Fiscal Policy On Expenditure Allocation And Attribute Preferences, Anirban Mukherjee, Andre Bonfrer Dec 2012

The Impact Of Macro Socio-Economic Drivers And Fiscal Policy On Expenditure Allocation And Attribute Preferences, Anirban Mukherjee, Andre Bonfrer

Research Collection Lee Kong Chian School Of Business

Our article investigates the effect of macro socio-economic drivers on Australian households’ allocation of expenditure in a category (household appliances) and conditional on the allocated category expenditure, preferences for products (clothes washers) within the category. At the category-level, we quantify the effect of changes in social mobility, disposable income, housing prices and the 2009 stimulus payments on purchase propensity and expenditure. At the product-level, we investigate how households trade off between price, energy efficiency and loading capacity conditional on allocated category expenditure, measuring nonhomotheticity in preferences. We use the model to study a number of hypothetical scenarios, where we simulate …


Banks' Survival During The Financial Crisis: The Role Of Regulatory Reporting Quality, Jeffrey Ng, Tjomme O. Rusticus Dec 2012

Banks' Survival During The Financial Crisis: The Role Of Regulatory Reporting Quality, Jeffrey Ng, Tjomme O. Rusticus

Research Collection School Of Accountancy

In this paper, we investigate the effect of bank transparency before the crisis on bank stability during the financial crisis that erupted in 2008. Using a large sample of private and public commercial banks in the United States, we find that transparency enhances stability. We use two measures of transparency. We develop a new measure of financial reporting transparency based on loan loss provision estimation errors. We corroborate our findings using a second measure based on the incidence of accounting restatements. We show that lower transparency before the crisis is associated with higher non-performing loans and lower profitability at the …


Eliciting Usable Gestures For Multi-Display Environments, Teddy Seyed, Chris Burns, Mario Costa Sousa, Frank Maurer, Anthony Tang Dec 2012

Eliciting Usable Gestures For Multi-Display Environments, Teddy Seyed, Chris Burns, Mario Costa Sousa, Frank Maurer, Anthony Tang

Research Collection School Of Computing and Information Systems

Multi-display environments (MDEs) have advanced rapidly in recent years, incorporating multi-touch tabletops, tablets, wall displays and even position tracking systems. Designers have proposed a variety of interesting gestures for use in an MDE, some of which involve a user moving their hands, arms, body or even a device itself. These gestures are often used as part of interactions to move data between the various components of an MDE, which is a longstanding research problem. But designers, not users, have created most of these gestures and concerns over implementation issues such as recognition may have influenced their design. We performed a …


Cross-Lingual Identification Of Ambiguous Discourse Connectives For Resource-Poor Language, Lanjun Zhou, Wei Gao, Binyang Li, Zhongyu Wei, Kam-Fai Wong Dec 2012

Cross-Lingual Identification Of Ambiguous Discourse Connectives For Resource-Poor Language, Lanjun Zhou, Wei Gao, Binyang Li, Zhongyu Wei, Kam-Fai Wong

Research Collection School Of Computing and Information Systems

The lack of annotated corpora brings limitations in research of discourse classification for many languages. In this paper, we present the first effort towards recognizing ambiguities of discourse connectives, which is fundamental to discourse classification for resource-poor language such as Chinese. A language independent framework is proposed utilizing bilingual dictionaries, Penn Discourse Treebank and parallel data between English and Chinese. We start from translating the English connectives to Chinese using a bi-lingual dictionary. Then, the ambiguities in terms of senses a connective may signal are estimated based on the ambiguities of English connectives and word alignment information. Finally, the ambiguity …


Visualization For Anomaly Detection And Data Management By Leveraging Network, Sensor And Gis Techniques, Zhaoxia Wang, Chee Seng Chong, Rick S. M. Goh, Wanqing Zhou, Dan Peng, Hoong Chor Chin Dec 2012

Visualization For Anomaly Detection And Data Management By Leveraging Network, Sensor And Gis Techniques, Zhaoxia Wang, Chee Seng Chong, Rick S. M. Goh, Wanqing Zhou, Dan Peng, Hoong Chor Chin

Research Collection School Of Computing and Information Systems

This paper studies the importance of visualization for discerning and interpreting patterns of data and its application for solving real problems, such as anomaly detection and data management. There are various ways to realize visualization to cater to the needs of numerous real life applications. Depending on needs, a combination of some of these ways may be required for presenting an effective visualization. The authors present visualization schemes for anomaly detection/condition monitoring and data management by leveraging network techniques and combining them with modern techniques such as sensor, database, mobile communication, GPS and GIS techniques. Two case studies are presented …


Finding Thoughtful Comments From Social Media, Gottipati Swapna, Jing Jiang Dec 2012

Finding Thoughtful Comments From Social Media, Gottipati Swapna, Jing Jiang

Research Collection School Of Computing and Information Systems

Online user comments contain valuable user opinions. Comments vary greatly in quality and detecting high quality comments is a subtask of opinion mining and summarization research. Finding attentive comments that provide some reasoning is highly valuable in understanding the user’s opinion particularly in sociopolitical opinion mining and aids policy makers, social organizations or government sectors in decision making. In this paper we study the problem of detecting thoughtful comments. We empirically study various textual features, discourse relations and relevance features to predict thoughtful comments. We use logistic regression model and test on the datasets related to sociopolitical content. We found …


Use Of Rss Feeds To Push The Online Content To Users, Dan Ma Dec 2012

Use Of Rss Feeds To Push The Online Content To Users, Dan Ma

Research Collection School Of Computing and Information Systems

Many websites use Really Simple Syndication (RSS) feeds to actively push their online content to users rather than waiting for users to pull the content passively. In this paper, I construct a theoretical game model to study the profitability of an RSS-PUSH delivery mechanism. The model assumes a general profit structure for websites and heterogeneous users. To access valuable online content, users incur a variety of costs. They choose either to visit the website in the conventional way (the PULL model) or, if it is supported by the website, to use RSS (the PUSH model). Interestingly, I show that although …


A Survey Of Recommender Systems In Twitter, Su Mon Kywe, Ee Peng Lim, Feida Zhu Dec 2012

A Survey Of Recommender Systems In Twitter, Su Mon Kywe, Ee Peng Lim, Feida Zhu

Research Collection School Of Computing and Information Systems

Twitter is a social information network where short messages or tweets are shared among a large number of users through a very simple messaging mechanism. With a population of more than 100M users generating more than 300M tweets each day, Twitter users can be easily overwhelmed by the massive amount of information available and the huge number of people they can interact with. To overcome the above information overload problem, recommender systems can be introduced to help users make the appropriate selection. Researchers have began to study recommendation problems in Twitter but their works usually address individual recommendation tasks. There …


Extracting And Normalizing Entity-Actions From Users' Comments, Swapna Gottipati, Jing Jiang Dec 2012

Extracting And Normalizing Entity-Actions From Users' Comments, Swapna Gottipati, Jing Jiang

Research Collection School Of Computing and Information Systems

With the growing popularity of opinion-rich resources on the Web, new opportunities and challenges arise and aid people in actively using such information to understand the opinions of others. Opinion mining process currently focuses on extracting the sentiments of the users on products, social, political and economical issues. In many instances, users not only express their sentiments but also contribute their ideas, requests and suggestions through comments. Such comments are useful for domain experts and are referred to as actionable content. Extracting actionable knowledge from online social media has attracted a growing interest from both academia and the industry. We …


Reputation As Public Policy For Internet Security: A Field Study, Qian Tang, Leigh L. Linden, John S. Quarterman, Andrew Whinston Dec 2012

Reputation As Public Policy For Internet Security: A Field Study, Qian Tang, Leigh L. Linden, John S. Quarterman, Andrew Whinston

Research Collection School Of Computing and Information Systems

Cybersecurity is a national priority in this big data era. Because of the lack of incentives and the existence of negative externality, companies often underinvest in addressing security risks and accidents, despite government and industry recommendations. In the present article, we propose a method that utilizes reputation through information disclosure to motivate companies to behave pro-socially, improving their Internet security. Using outbound spam as a proxy for Internet security, we conducted a quasiexperimental field study for eight countries through SpamRankings.net. This outgoingspam-based study shows that information disclosure on outgoing spam can help reduce outgoing spam, approximately by 16 percent. This …


Do Hackers Seek Variety? An Empirical Analysis Of Website Defacements, Kok Wei Ooi, Seung-Hyun Kim, Qiu-Hong Wang, Kai Lung Hui Dec 2012

Do Hackers Seek Variety? An Empirical Analysis Of Website Defacements, Kok Wei Ooi, Seung-Hyun Kim, Qiu-Hong Wang, Kai Lung Hui

Research Collection School Of Computing and Information Systems

The importance of securing the cyberspace is higher than ever along with the evolution of cyber attacks launched by hackers with malicious intention. However, there has been little research to understand the hackers who are the most important agents determining the landscape of information security. This paper investigates the behaviors of hackers using a longitudinal dataset of defacement attacks. Based on theories of economics of criminal behaviors and variety seeking, we find that hackers seek variety in choosing their victims in terms of region, hacking method, and the type of operating systems; as their prior experience is focused in terms …


Lagrangian Relaxation For Large-Scale Multi-Agent Planning, Geoffrey J. Gordon, Pradeep Varakantham, William Yeoh, Hoong Chuin Lau, Ajay S. Aravamudhan, Shih-Fen Cheng Dec 2012

Lagrangian Relaxation For Large-Scale Multi-Agent Planning, Geoffrey J. Gordon, Pradeep Varakantham, William Yeoh, Hoong Chuin Lau, Ajay S. Aravamudhan, Shih-Fen Cheng

Research Collection School Of Computing and Information Systems

Multi-agent planning is a well-studied problem with various applications including disaster rescue, urban transportation and logistics, both for autonomous agents and for decision support to humans. Due to computational constraints, existing research typically focuses on one of two scenarios: unstructured domains with many agents where we are content with heuristic solutions, or domains with small numbers of agents or special structure where we can provide provably near-optimal solutions. By contrast, in this paper, we focus on providing provably near-optimal solutions for domains with large numbers of agents, by exploiting a common domain-general property: if individual agents each have limited influence …


B-Cell Epitope Prediction Through A Graph Model, Liang Zhao, Limsoon Wong, Lanyuan Lu, Steven C. H. Hoi, Jinyan Li Dec 2012

B-Cell Epitope Prediction Through A Graph Model, Liang Zhao, Limsoon Wong, Lanyuan Lu, Steven C. H. Hoi, Jinyan Li

Research Collection School Of Computing and Information Systems

Prediction of B-cell epitopes from antigens is useful to understand the immune basis of antibody-antigen recognition, and is helpful in vaccine design and drug development. Tremendous efforts have been devoted to this long-studied problem, however, existing methods have at least two common limitations. One is that they only favor prediction of those epitopes with protrusive conformations, but show poor performance in dealing with planar epitopes. The other limit is that they predict all of the antigenic residues of an antigen as belonging to one single epitope even when multiple non-overlapping epitopes of an antigen exist.


Structural And Functional Analysis Of Multi-Interface Domains, Liang Zhao, Steven C. H. Hoi, Limsoon Wong, Tobias Hamp, Jinyan Li Dec 2012

Structural And Functional Analysis Of Multi-Interface Domains, Liang Zhao, Steven C. H. Hoi, Limsoon Wong, Tobias Hamp, Jinyan Li

Research Collection School Of Computing and Information Systems

A multi-interface domain is a domain that can shape multiple and distinctive binding sites to contact with many other domains, forming a hub in domain-domain interaction networks. The functions played by the multiple interfaces are usually different, but there is no strict bijection between the functions and interfaces as some subsets of the interfaces play the same function. This work applies graph theory and algorithms to discover fingerprints for the multiple interfaces of a domain and to establish associations between the interfaces and functions, based on a huge set of multi-interface proteins from PDB. We found that about 40% of …


Cost-Sensitive Online Classification, Jialei Wang, Peilin Zhao, Steven C. H. Hoi Dec 2012

Cost-Sensitive Online Classification, Jialei Wang, Peilin Zhao, Steven C. H. Hoi

Research Collection School Of Computing and Information Systems

Both cost-sensitive classification and online learning have been extensively studied in data mining and machine learning communities, respectively. However, very limited study addresses an important intersecting problem, that is, “Cost-Sensitive Online Classification". In this paper, we formally study this problem, and propose a new framework for Cost-Sensitive Online Classification by directly optimizing cost-sensitive measures using online gradient descent techniques. Specifically, we propose two novel cost-sensitive online classification algorithms, which are designed to directly optimize two well-known cost-sensitive measures: (i) maximization of weighted sum of sensitivity and specificity, and (ii) minimization of weighted misclassification cost. We analyze the theoretical bounds of …


Agent-Based Virtual Humans In Co-Space: An Evaluative Study, Yilin Kang, Ah-Hwee Tan, Fiona Fui-Hoon Nah Dec 2012

Agent-Based Virtual Humans In Co-Space: An Evaluative Study, Yilin Kang, Ah-Hwee Tan, Fiona Fui-Hoon Nah

Research Collection School Of Computing and Information Systems

Co-Space refers to interactive virtual environment modelled after the real world in terms of look-and-feel, functionalities and services. We have developed a 3D virtual world named Nan yang Technological University (NTU) Co-Space populated with virtual human characters. Three key requirements of realistic virtual humans in the virtual world have been identified, namely (1) autonomy: agents can function on their own, (2) interactivity: agents can interact naturally with players, and (3) personality: agents can exhibit human traits and characteristics. Working towards these challenges, we propose a brain-inspired agent architecture that integrates goal-directed autonomy, natural language interaction and human-like personality. We conducted …