Structural And Functional Analysis Of Multi-Interface Domains,
2012
Nanyang Technological University
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,
2012
Nanyang Technological University
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,
2012
Singapore Management University
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 …
Investigating Intelligent Agents In A 3d Virtual World,
2012
Singapore Management University
Investigating Intelligent Agents In A 3d Virtual World, Yilin Kang, Fiona Fui-Hoon Nah, Ah-Hwee Tan
Research Collection School Of Computing and Information Systems
Web 3.0 involves "intelligent" web applications that utilize natural language processing, machine-based learning and reasoning, and intelligent techniques to analyze and understand user behavior. In this research, we empirically assess a specific form of Web 3.0 application in the form of intelligent agents that offer assistance to users in the virtual world. Using media naturalness theory, we hypothesize that the use of intelligent agents in the virtual world can enhance user experience by offering a more natural way of communication and assistance to users. We are interested to test if media naturalness theory holds in the context of intelligent agents …
Knowledge-Based Exploration For Reinforcement Learning In Self-Organizing Neural Networks,
2012
Singapore Management University
Knowledge-Based Exploration For Reinforcement Learning In Self-Organizing Neural Networks, Teck-Hou Teng, Ah-Hwee Tan
Research Collection School Of Computing and Information Systems
Exploration is necessary during reinforcement learning to discover new solutions in a given problem space. Most reinforcement learning systems, however, adopt a simple strategy, by randomly selecting an action among all the available actions. This paper proposes a novel exploration strategy, known as Knowledge-based Exploration, for guiding the exploration of a family of self-organizing neural networks in reinforcement learning. Specifically, exploration is directed towards unexplored and favorable action choices while steering away from those negative action choices that are likely to fail. This is achieved by using the learned knowledge of the agent to identify prior action choices leading to …
Data Mining Of Pancreatic Cancer Protein Databases,
2012
University of Nebraska-Lincoln
Data Mining Of Pancreatic Cancer Protein Databases, Peter Revesz, Christopher Assi
School of Computing: Conference and Workshop Papers
Data mining of protein databases poses special challenges because many protein databases are non- relational whereas most data mining and machine learning algorithms assume the input data to be a type of rela- tional database that is also representable as an ARFF file. We developed a method to restructure protein databases so that they become amenable for various data mining and machine learning tools. Our restructuring method en- abled us to apply both decision tree and support vector machine classifiers to a pancreatic protein database. The SVM classifier that used both GO term and PFAM families to characterize proteins gave …
Detecting Anomalies In Bipartite Graphs With Mutual Dependency Principles,
2012
Singapore Management University
Detecting Anomalies In Bipartite Graphs With Mutual Dependency Principles, Hanbo Dai, Feida Zhu, Ee Peng Lim, Hwee Hwa Pang
Research Collection School Of Computing and Information Systems
Bipartite graphs can model many real life applications including users-rating-products in online marketplaces, users-clicking-webpages on the World Wide Web and users referring users in social networks. In these graphs, the anomalousness of nodes in one partite often depends on that of their connected nodes in the other partite. Previous studies have shown that this dependency can be positive (the anomalousness of a node in one partite increases or decreases along with that of its connected nodes in the other partite) or negative (the anomalousness of a node in one partite rises or falls in opposite direction to that of its …
Effect Of Business Intelligence And It Infrastructure Flexibility On Organizational Agility,
2012
Singapore Management University
Effect Of Business Intelligence And It Infrastructure Flexibility On Organizational Agility, Xiaofeng Chen, Keng Siau
Research Collection School Of Computing and Information Systems
There is a growing use of business intelligence (BI) for better management decisions in different industries. However, empirical studies on BI are still scarce in academic research. This research investigates BI from an organizational agility perspective. Organizational agility is the ability to sense and respond to market opportunities and threats with speed. Drawing on systems theory and literature on organizational agility, business intelligence, and IT infrastructure flexibility, we hypothesize that BI use and IT infrastructure flexibility are two major antecedents to organizational agility. We developed a research model to examine the effect of BI use and IT infrastructure flexibility on …
Critical Success Factors Of Location-Based Services,
2012
Singapore Management University
Critical Success Factors Of Location-Based Services, Natalie J. P. Chin, Keng Siau
Research Collection School Of Computing and Information Systems
Location-based services evolved with the advancement in mobile technology and wireless technology. Researchers have studied location-based services in terms of privacy, trust, and user acceptance. Statistics suggest the percentage of location-based services users is still relatively low. Therefore, the main objective of this study was to gain a comprehensive and holistic understanding of the critical success factors of location-based services. The electronic brainstorming approach was used to gather the opinions of an expert group of practitioners, researchers, and users on the critical success factors of location-based services. Through grouping similar factors together based on past literature, 15 categories of critical …
On Recommending Hashtags In Twitter Networks,
2012
Singapore Management University
On Recommending Hashtags In Twitter Networks, Su Mon Kywe, Tuan-Anh Hoang, Ee Peng Lim, Feida Zhu
Research Collection School Of Computing and Information Systems
Twitter network is currently overwhelmed by massive amount of tweets generated by its users. To effectively organize and search tweets, users have to depend on appropriate hashtags inserted into tweets. We begin our research on hashtags by first analyzing a Twitter dataset generated by more than 150,000 Singapore users over a three-month period. Among several interesting findings about hashtag usage by this user community, we have found a consistent and significant use of new hashtags on a daily basis. This suggests that most hashtags have very short life span. We further propose a novel hashtag recommendation method based on collaborative …
Demonstration: Dynamic Sensor Registration And Semantic Processing For Ad-Hoc Mobile Environments (Semmob),
2012
Wright State University - Main Campus
Demonstration: Dynamic Sensor Registration And Semantic Processing For Ad-Hoc Mobile Environments (Semmob), Pramod Anantharam, Gary Alan Smith, Josh Pschorr, Krishnaprasad Thirunarayan, Amit P. Sheth
Kno.e.sis Publications
SemMOB enables dynamic registration of sensors via mobile devices, search, and near real-time inference over sensor observations in ad-hoc mobile environments (e.g., fire fighting). We demonstrate SemMOB in the context of an emergency response use case that requires automatic and dynamic registrations of sensor devices and annotation of sensor observations, decoding of latitude-longitude information in terms of human sensible names, fusion and abstraction of sensor values using background knowledge, and their visualization using mash-up.
Using Social Influence To Predict Subscriber Churn,
2012
Wright State University - Main Campus
Using Social Influence To Predict Subscriber Churn, Derek Doran, Veena Mendiratta, Chitra Phadke, Dan Kushnir, Huseyin Uzunalioglu
Kno.e.sis Publications
The saturation of mobile phone markets has resulted in rising costs for operators to obtain new customers. These operators thus focus their energies on identifying users that will churn so they can be targeted for retention campaigns. Typical churn prediction algorithms identify churners based on service usage metrics, network performance indicators, and demographic information. Social and peer-influence to churn, however, is usually not considered. In this paper, we describe a new churn prediction algorithm that incorporates the influence churners spread to their social peers. Using data from a major service provider, we show that social influence improves churn prediction and …
Understanding User Triads On Facebook,
2012
Wright State University - Main Campus
Understanding User Triads On Facebook, Derek Doran, Alberta De La Rosa Algarin, Swapna S. Gokhale
Kno.e.sis Publications
Contemporary approaches that analyze user behavior on online social networks only consider interactions among dyads, which are pairs of directly connected users. A large body of sociological work, however, suggests that mutual connections among users can influence their activities, leading to differences between two- and three-way interactions. This paper explores the dynamics of triads among Facebook users based on the wall posts from the New Orleans regional network. Initially, each connection is categorized as a close friendship or an acquiantance, contingent on the number of wall posts exchanged. Subsequently, the impact of different types of connections comprising triads is examined …
Linked Data Demystified: Practical Efforts To Transform Contentdm Metadata For The Linked Data Cloud,
2012
University of Nevada, Las Vegas
Linked Data Demystified: Practical Efforts To Transform Contentdm Metadata For The Linked Data Cloud, Silvia B. Southwick, Cory K. Lampert
Library Faculty Presentations
The library literature and events like the ALA Annual Conference have been inundated with presentations and articles on linked data. At UNLV Libraries, we understand the importance of linked data in helping to better service our users. We have designed and initiated a pilot project to apply linked data concepts to the practical task of transforming a sample set of our CONTENTdm digital collections data into future-oriented linked data. This presentation will outline rationale for beginning work in linked data and detail the phases we will undertake in the proof of concept project. We hope through this research experiment to …
Audit Mechanisms For Provable Risk Management And Accountable Data Governance,
2012
Singapore Management University
Audit Mechanisms For Provable Risk Management And Accountable Data Governance, Jeremiah Blocki, Nicolas Christin, Anupam Datta, Arunesh Sinha
Research Collection School Of Computing and Information Systems
Organizations that collect and use large volumes of personal information are expected under the principle of accountable data governance to take measures to protect data subjects from risks that arise from inapproriate uses of this information. In this paper, we focus on a specific class of mechanisms—audits to identify policy violators coupled with punishments—that organizations such as hospitals, financial institutions, and Web services companies may adopt to protect data subjects from privacy and security risks stemming from inappropriate information use by insiders. We model the interaction between the organization (defender) and an insider (adversary) during the audit process as a …
Joint Topic Modeling For Event Summarization Across News And Social Media Streams,
2012
Singapore Management University
Joint Topic Modeling For Event Summarization Across News And Social Media Streams, Wei Gao, Peng Li, Kareem Darwish
Research Collection School Of Computing and Information Systems
Social media streams such as Twitter are regarded as faster first-hand sources of information generated by massive users. The content diffused through this channel, although noisy, provides important complement and sometimes even a substitute to the traditional news media reporting. In this paper, we propose a novel unsupervised approach based on topic modeling to summarize trending subjects by jointly discovering the representative and complementary information from news and tweets. Our method captures the content that enriches the subject matter by reinforcing the identification of complementary sentence-tweet pairs. To valuate the complementarity of a pair, we leverage topic modeling formalism by …
How I Would Like Semantic Web To Be, For My Children.,
2012
Wright State University - Main Campus
How I Would Like Semantic Web To Be, For My Children., Raghava Mutharaju
Kno.e.sis Publications
Semantic Web, since its inception, has gone through lot of developments in its relatively nascent existence; right from people's perception, to the standards and to its adoption by the industry and more importantly by the scientific community. This impressive growth only seems to increase. In this paper, we project this growth to the next 10 years and highlight some of the facets on which Semantic Web could have a major impact on. We also present the challenges that Semantic Web and its community has to deal with in order to get there.
An Efficient Bit Vector Approach To Semantics-Based Machine Perception In Resource-Constrained Devices,
2012
Wright State University - Main Campus
An Efficient Bit Vector Approach To Semantics-Based Machine Perception In Resource-Constrained Devices, Cory Andrew Henson, Krishnaprasad Thirunarayan, Amit P. Sheth
Kno.e.sis Publications
The primary challenge of machine perception is to define efficient computational methods to derive high-level knowledge from low-level sensor observation data. Emerging solutions are using ontologies for expressive representation of concepts in the domain of sensing and perception, which enable advanced integration and interpretation of heterogeneous sensor data. The computational complexity of OWL, however, seriously limits its applicability and use within resource-constrained environments, such as mobile devices. To overcome this issue, we employ OWL to formally define the inference tasks needed for machine perception – explanation and discrimination – and then provide efficient algorithms for these tasks, using bit-vector encodings …
Iexplore: Interactive Browsing And Exploring Biomedical Knowledge,
2012
Wright State University - Main Campus
Iexplore: Interactive Browsing And Exploring Biomedical Knowledge, Vinh Nguyen, Olivier Bodenreider, Jagannathan Srinivasan, Todd Minning, Thomas Rindflesch, Bastien Rance, Ramakanth Kavuluru, Himi Yalamanchili, Krishnaprasad Thirunarayan, Satya S. Sahoo, Amit P. Sheth
Kno.e.sis Publications
We present iExplore, a Semantic Web based application that helps biomedical researchers study and explore biomedical knowledge interactively. iExplore uses the Biomedical Knowledge Repository (BKR), which integrates knowledge from various sources ranging from information extracted from biomedical literature (from PubMed) to many structured vocabularies in the Unified Medical Language System (UMLS). The current version of BKR provides a unified provenance representation for 12 million semantic predications (triples with a predicate connecting a subject and an object) derived from 87 vocabulary families in the UMLS and 14 million predications extracted from 21 million PubMed abstracts. To engage the domain experts in …
Mining Coherent Anomaly Collections On Web Data,
2012
Singapore Management University
Mining Coherent Anomaly Collections On Web Data, Hanbo Dai, Feida Zhu, Ee-Peng Lim, Hwee Hwa Pang
Research Collection School Of Computing and Information Systems
The recent boom of weblogs and social media has attached increasing importance to the identification of suspicious users with unusual behavior, such as spammers or fraudulent reviewers. A typical spamming strategy is to employ multiple dummy accounts to collectively promote a target, be it a URL or a product. Consequently, these suspicious accounts exhibit certain coherent anomalous behavior identifiable as a collection. In this paper, we propose the concept of Coherent Anomaly Collection (CAC) to capture this kind of collections, and put forward an efficient algorithm to simultaneously find the top-K disjoint CACs together with their anomalous behavior patterns. Compared …
