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Articles 5431 - 5460 of 7256
Full-Text Articles in Computer Sciences
Ssnetviz: A Visualization Engine For Heterogeneous Semantic Social Networks, Ee Peng Lim, Maureen Maureen, Nelman Lubis Ibrahim, Aixin Sun, Anwitaman Datta, Kuiyu Chang
Ssnetviz: A Visualization Engine For Heterogeneous Semantic Social Networks, Ee Peng Lim, Maureen Maureen, Nelman Lubis Ibrahim, Aixin Sun, Anwitaman Datta, Kuiyu Chang
Research Collection School Of Computing and Information Systems
SSnetViz is an ongoing research to design and implement a visualization engine for heterogeneous semantic social networks. A semantic social network is a multi-modal network that contains nodes representing di®erent types of people or object entities, and edges representing relationships among them. When multiple heterogeneous semantic social networks are to be visualized together, SSnetViz provides a suite of functions to store heterogeneous semantic social networks, to integrate them for searching and analysis. We will illustrate these functions using social networks related to terrorism research, one crafted by domain experts and another from Wikipedia.
Setting Discrete Bid Levels Adaptively In Repeated Auctions, Jilian Zhang, Hoong Chuin Lau, Jialie Shen
Setting Discrete Bid Levels Adaptively In Repeated Auctions, Jilian Zhang, Hoong Chuin Lau, Jialie Shen
Research Collection School Of Computing and Information Systems
The success of an auction design often hinges on its ability to set parameters such as reserve price and bid levels that will maximize an objective function such as the auctioneer revenue. Works on designing adaptive auction mechanisms have emerged recently, and the challenge is in learning different auction parameters by observing the bidding in previous auctions. In this paper, we propose a non-parametric method for determining discrete bid levels dynamically so as to maximize the auctioneer revenue. First, we propose a non-parametric kernel method for estimating the probabilities of closing price with past auction data. Then a greedy strategy …
A Distributed Spatial Index For Error-Prone Wireless Data Broadcast, Baihua Zheng, Wang-Chien Lee, Ken C. K. Lee, Dik Lun Lee, Min Shao
A Distributed Spatial Index For Error-Prone Wireless Data Broadcast, Baihua Zheng, Wang-Chien Lee, Ken C. K. Lee, Dik Lun Lee, Min Shao
Research Collection School Of Computing and Information Systems
Information is valuable to users when it is available not only at the right time but also at the right place. To support efficient location-based data access in wireless data broadcast systems, a distributed spatial index (called DSI) is presented in this paper. DSI is highly efficient because it has a linear yet fully distributed structure that naturally shares links in different search paths. DSI is very resilient to the error-prone wireless communication environment because interrupted search operations based on DSI can be resumed easily. It supports search algorithms for classical location-based queries such as window queries and kNN queries …
On Efficient Mutual Nearest Neighbor Query Processing In Spatial Databases, Yunjun Gao, Baihua Zheng, Gencai Chen, Qing Li
On Efficient Mutual Nearest Neighbor Query Processing In Spatial Databases, Yunjun Gao, Baihua Zheng, Gencai Chen, Qing Li
Research Collection School Of Computing and Information Systems
This paper studies a new form of nearest neighbor queries in spatial databases, namely, mutual nearest neighbour (MNN) search. Given a set D of objects and a query object q, an MNN query returns from D, the set of objects that are among the k1 (≥ 1) nearest neighbors (NNs) of q; meanwhile, have q as one of their k2(≥ 1) NNs. Although MNN queries are useful in many applications involving decision making, data mining, and pattern recognition, it cannot be efficiently handled by existing spatial query processing approaches. In this paper, we present …
Optimal-Location-Selection Query Processing In Spatial Databases, Yunjun Gao, Baihua Zheng, Gencai Chen, Qing Li
Optimal-Location-Selection Query Processing In Spatial Databases, Yunjun Gao, Baihua Zheng, Gencai Chen, Qing Li
Research Collection School Of Computing and Information Systems
This paper introduces and solves a novel type of spatial queries, namely, Optimal-Location-Selection (OLS) search, which has many applications in real life. Given a data object set D_A, a target object set D_B, a spatial region R, and a critical distance d_c in a multidimensional space, an OLS query retrieves those target objects in D_B that are outside R but have maximal optimality. Here, the optimality of a target object b \in D_B located outside R is defined as the number of the data objects from D_A that are inside R and meanwhile have their distances to b not exceeding …
A Fair Assignment Algorithm For Multiple Preference Queries, Leong Hou U, Nikos Mamoulis, Kyriakos Mouratidis
A Fair Assignment Algorithm For Multiple Preference Queries, Leong Hou U, Nikos Mamoulis, Kyriakos Mouratidis
Research Collection School Of Computing and Information Systems
Consider an internship assignment system, where at the end of each academic year, interested university students search and apply for available positions, based on their preferences (e.g., nature of the job, salary, office location, etc). In a variety of facility, task or position assignment contexts, users have personal preferences expressed by different weights on the attributes of the searched objects. Although individual preference queries can be evaluated by selecting the object in the database with the highest aggregate score, in the case of multiple simultaneous requests, a single object cannot be assigned to more than one users. The challenge is …
Scalable Verification For Outsourced Dynamic Databases, Hwee Hwa Pang, Jilian Zhang, Kyriakos Mouratidis
Scalable Verification For Outsourced Dynamic Databases, Hwee Hwa Pang, Jilian Zhang, Kyriakos Mouratidis
Research Collection School Of Computing and Information Systems
Query answers from servers operated by third parties need to be verified, as the third parties may not be trusted or their servers may be compromised. Most of the existing authentication methods construct validity proofs based on the Merkle hash tree (MHT). The MHT, however, imposes severe concurrency constraints that slow down data updates. We introduce a protocol, built upon signature aggregation, for checking the authenticity, completeness and freshness of query answers. The protocol offers the important property of allowing new data to be disseminated immediately, while ensuring that outdated values beyond a pre-set age can be detected. We also …
Inferring Player Rating From Performance Data In Massively Multiplayer Online Role-Playing Games (Mmorpgs), Kyong Jin Shim, Muhammad Aurangzeb Ahmad, Nishith Pathak, Jaideep Srivastava
Inferring Player Rating From Performance Data In Massively Multiplayer Online Role-Playing Games (Mmorpgs), Kyong Jin Shim, Muhammad Aurangzeb Ahmad, Nishith Pathak, Jaideep Srivastava
Research Collection School Of Computing and Information Systems
This paper examines online player performance in EverQuest II, a popular massively multiplayer online role-playing game (MMORPG) developed by Sony Online Entertainment. The study uses the game's player performance data to devise performance metrics for online players. We report three major findings. First, we show that the game's point-scaling system overestimates performances of lower level players and underestimates performances of higher level players. We present a novel point-scaling system based on the game's player performance data that addresses the underestimation and overestimation problems. Second, we present a highly accurate predictive model for player performance as a function of past behavior. …
Symphony: Enabling Search-Driven Applications, John C. Shafer, Rakesh Agrawal, Hady W. Lauw
Symphony: Enabling Search-Driven Applications, John C. Shafer, Rakesh Agrawal, Hady W. Lauw
Research Collection School Of Computing and Information Systems
We present the design of Symphony, a platform that enables non-developers to build and deploy a new class of search-driven applications that combine their data and domain expertise with content from search engines and other web services. The Symphony prototype has been built on top of Microsoft’s Live Search infrastructure. While Symphony naturally makes use of the customization capabilities exposed by Live Search, its distinguishing feature is the capability it provides to the application creator to combine their proprietary data and domain expertise with content obtained from Live Search. They can also integrate specialized data obtained from web services to …
Are Male And Female Avatars Perceived Equally In 3-D Virtual Worlds?, David Dewester, Fiona Fui-Hoon Nah, Sarah Gervais, Keng Siau
Are Male And Female Avatars Perceived Equally In 3-D Virtual Worlds?, David Dewester, Fiona Fui-Hoon Nah, Sarah Gervais, Keng Siau
Research Collection School Of Computing and Information Systems
Virtual worlds are three-dimensional, computer-generated worlds in which users take the form of avatars and use those avatars to interact with objects and other avatars in the virtual world. Virtual worlds are growing in importance in both educational institutions and businesses. Educational institutions have adopted virtual worlds as a medium for instructional delivery whereas businesses are using virtual worlds for recruitment, training, collaboration, and marketing. Given these emerging phenomena, a better understanding of behavioral and perceptual issues in virtual worlds is warranted. We propose a research model to study the interaction effects of gender stereotypicality of male and female avatars …
3-D Virtual Worlds And Higher Education, X. Chen, Keng Siau, Fiona Fui-Hoon Nah
3-D Virtual Worlds And Higher Education, X. Chen, Keng Siau, Fiona Fui-Hoon Nah
Research Collection School Of Computing and Information Systems
Conducting education in three-dimensional (3-D) virtual worlds is an emerging phenomenon in the educational arena. The objective of this research is to investigate the factors influencing students’ intention to adopt the 3-D virtual worlds for delivery of education. Drawing on existing technology acceptance models as well as studies in traditional and distance education, we developed a model to study students’ acceptance of using a 3-D virtual world for education and propose to test the model empirically using survey data collected from college students. We also study the use of two instructional methods in the 3-D virtual world. This study contributes …
Measuring Method Complexity: Uml Versus Bpmn, Jan Recker, Michael Zur Muehlen, Keng Siau, John Erickson, Marta Indulska
Measuring Method Complexity: Uml Versus Bpmn, Jan Recker, Michael Zur Muehlen, Keng Siau, John Erickson, Marta Indulska
Research Collection School Of Computing and Information Systems
Graphical models are used to depict relevant aspects of real-world domains intended to be supported by an information system. Various approaches for modeling exist and approaches such as object-oriented and process-oriented modeling methods are in widespread use. These modeling methods differ in their expressive power as well as in their complexity of use, thereby leading to an important investment decision for organizations seeking to conduct modeling projects. In this paper, we used an established approach for evaluating the complexity of conceptual modeling methods and compared two important industry standards for modeling, Unified Modeling Language and Business Process Modeling Notation, based …
Open Forum: The Future Of Library Systems, Maria Collins, Andrée J. Rathemacher
Open Forum: The Future Of Library Systems, Maria Collins, Andrée J. Rathemacher
Technical Services Faculty Publications
Moderated by Maria Collins of North Carolina State University, discussion at this open forum on the future of library systems touched on open-source library systems, cloud computing, new initiatives by the Open Library Environment (OLE) Project and OCLC, and desired characteristics of future integrated library systems. Most participants had limited experience with next-generation library systems and attended the open forum with the desire to broaden their understanding, although some were exposed to or had worked with the open-source discovery tool VuFind, the OLE Project, WorldCat Local, and the OCLC Web-scale service. A strong desire to customize library systems to meet …
“Best K”: Critical Clustering Structures In Categorical Datasets, Keke Chen, Ling Liu
“Best K”: Critical Clustering Structures In Categorical Datasets, Keke Chen, Ling Liu
Kno.e.sis Publications
The demand on cluster analysis for categorical data continues to grow over the last decade. A well-known problem in categorical clustering is to determine the best K number of clusters. Although several categorical clustering algorithms have been developed, surprisingly, none has satisfactorily addressed the problem of best K for categorical clustering. Since categorical data does not have an inherent distance function as the similarity measure, traditional cluster validation techniques based on geometric shapes and density distributions are not appropriate for categorical data. In this paper, we study the entropy property between the clustering results of categorical data with different K …
Tableau Algorithm For Concept Satisfiability In Description Logic Alch, Satya S. Sahoo, Krishnaprasad Thirunarayan
Tableau Algorithm For Concept Satisfiability In Description Logic Alch, Satya S. Sahoo, Krishnaprasad Thirunarayan
Kno.e.sis Publications
The provenir ontology is an upper-level ontology to facilitate interoperability of provenance information in scientific applications. The description logic (DL) expressivity of provenir ontology is ALCH, that is, it models role hierarchies (H) (without transitive roles and inverse roles). Even though the complexity results for concept satisfiability for numerous variants of DL such as ALC with transitively closed roles (ALCR+ also called S), inverse roles SI, and role hierarchy SHI have been well-established, similar results for ALCH has been surprisingly missing from the literature. Here, we show that the complexity of the concept satisfiability problem for the ALCH variant …
Continuous Obstructed Nearest Neighbor Queries In Spatial Databases, Yunjun Gao, Baihua Zheng
Continuous Obstructed Nearest Neighbor Queries In Spatial Databases, Yunjun Gao, Baihua Zheng
Research Collection School Of Computing and Information Systems
In this paper, we study a novel form of continuous nearest neighbor queries in the presence of obstacles, namely continuous obstructed nearest neighbor (CONN) search. It considers the impact of obstacles on the distance between objects, which is ignored by most of spatial queries. Given a data set P, an obstacle set O, and a query line segment q in a two-dimensional space, a CONN query retrieves the nearest neighbor of each point on q according to the obstructed distance, i.e., the shortest path between them without crossing any obstacle. We formulate CONN search, analyze its unique properties, and develop …
Compositemap: A Novel Framework For Music Similarity Measure, Bingjun Zhang, Jialie Shen, Qiaoliang Xiang, Ye Wang
Compositemap: A Novel Framework For Music Similarity Measure, Bingjun Zhang, Jialie Shen, Qiaoliang Xiang, Ye Wang
Research Collection School Of Computing and Information Systems
With the continuing advances in data storage and communication technology, there has been an explosive growth of music information from different application domains. As an effective technique for organizing, browsing, and searching large data collections, music information retrieval is attracting more and more attention. How to measure and model the similarity between different music items is one of the most fundamental yet challenging research problems. In this paper, we introduce a novel framework based on a multimodal and adaptive similarity measure for various applications. Distinguished from previous approaches, our system can effectively combine music properties from different aspects into a …
Spatial Cloaking Revisited: Distinguishing Information Leakage From Anonymity, Kar Way Tan, Yimin Lin, Kyriakos Mouratidis
Spatial Cloaking Revisited: Distinguishing Information Leakage From Anonymity, Kar Way Tan, Yimin Lin, Kyriakos Mouratidis
Research Collection School Of Computing and Information Systems
Location-based services (LBS) are receiving increasing popularity as they provide convenience to mobile users with on-demand information. The use of these services, however, poses privacy issues as the user locations and queries are exposed to untrusted LBSs. Spatial cloaking techniques provide privacy in the form of k-anonymity; i.e., they guarantee that the (location of the) querying user u is indistinguishable from at least k-1 others, where k is a parameter specified by u at query time. To achieve this, they form a group of k users, including u, and forward their minimum bounding rectangle (termed anonymzing spatial region, ASR) to …
Learning And Inferencing In User Ontology For Personalized Semantic Web Search, Xing Jiang, Ah-Hwee Tan
Learning And Inferencing In User Ontology For Personalized Semantic Web Search, Xing Jiang, Ah-Hwee Tan
Research Collection School Of Computing and Information Systems
User modeling is aimed at capturing the users’ interests in a working domain, which forms the basis of providing personalized information services. In this paper, we present an ontology based user model, called user ontology, for providing personalized information service in the Semantic Web. Different from the existing approaches that only use concepts and taxonomic relations for user modeling, the proposed user ontology model utilizes concepts, taxonomic relations, and non-taxonomic relations in a given domain ontology to capture the users’ interests. As a customized view of the domain ontology, a user ontology provides a richer and more precise representation of …
Active Learning For Causal Bayesian Network Structure With Non-Symmetrical Entropy, Li G., Tze-Yun Leong
Active Learning For Causal Bayesian Network Structure With Non-Symmetrical Entropy, Li G., Tze-Yun Leong
Research Collection School Of Computing and Information Systems
Causal knowledge is crucial for facilitating comprehension, diagnosis, prediction, and control in automated reasoning. Active learning in causal Bayesian networks involves interventions by manipulating specific variables, and observing the patterns of change over other variables to derive causal knowledge. In this paper, we propose a new active learning approach that supports interventions with node selection. Our method admits a node selection criterion based on non-symmetrical entropy from the current data and a stop criterion based on structure entropy of the resulting networks. We examine the technical challenges and practical issues involved. Experimental results on a set of benchmark Bayesian networks …
Bonus Plans Of Mice And Men, M. Thulasidas
Bonus Plans Of Mice And Men, M. Thulasidas
Research Collection School Of Computing and Information Systems
Our best-laid plans often go awry. We see it all the time at a personal level -- accidents (both good and bad), deaths (both of loved ones and rich uncles), births, and lotteries all conspire to reshuffle our priorities and render our plans null and void. In fact, there is nothing like a solid misfortune to get us to put things in perspective. This opportunity may be the proverbial silver lining we are constantly advised to see. What is true at a personal level holds true also at a larger scale. The industry-wide financial meltdown has imparted a philosophical clarity …
A Bayesian Approach Integrating Regional And Global Features For Image Semantic Learning, Luong-Dong Nguyen, Ghim-Eng Yap, Ying Liu, Ah-Hwee Tan, Liang-Tien Chia, Joo-Hwee Lim
A Bayesian Approach Integrating Regional And Global Features For Image Semantic Learning, Luong-Dong Nguyen, Ghim-Eng Yap, Ying Liu, Ah-Hwee Tan, Liang-Tien Chia, Joo-Hwee Lim
Research Collection School Of Computing and Information Systems
In content-based image retrieval, the “semantic gap” between visual image features and user semantics makes it hard to predict abstract image categories from low-level features. We present a hybrid system that integrates global features (Gfeatures) and region features (R-features) for predicting image semantics. As an intermediary between image features and categories, we introduce the notion of mid-level concepts, which enables us to predict an image’s category in three steps. First, a G-prediction system uses G-features to predict the probability of each category for an image. Simultaneously, a R-prediction system analyzes R-features to identify the probabilities of mid-level concepts in that …
Ontology Supported Knowledge Discovery In The Field Of Human Performance And Cognition, Christopher Thomas, Pablo N. Mendes, Delroy H. Cameron, Amit P. Sheth, Krishnaprasad Thirunarayan, Cartic Ramakrishnan
Ontology Supported Knowledge Discovery In The Field Of Human Performance And Cognition, Christopher Thomas, Pablo N. Mendes, Delroy H. Cameron, Amit P. Sheth, Krishnaprasad Thirunarayan, Cartic Ramakrishnan
Kno.e.sis Publications
No abstract provided.
Analysis And Monetization Of Social Data, Amit P. Sheth
Analysis And Monetization Of Social Data, Amit P. Sheth
Kno.e.sis Publications
No abstract provided.
Extending Sparql To Support Spatially And Temporally Related Information, Prateek Jain, Amit P. Sheth, Peter Z. Yeh, Kunal Verma
Extending Sparql To Support Spatially And Temporally Related Information, Prateek Jain, Amit P. Sheth, Peter Z. Yeh, Kunal Verma
Kno.e.sis Publications
No abstract provided.
A Functional Framework For Content Management, Robert Emer Broadbent
A Functional Framework For Content Management, Robert Emer Broadbent
Theses and Dissertations
This thesis proposes a functional framework for content management. This framework provides concepts and vocabulary for analysis and description of content management systems. The framework is derived from an analysis of eight content management systems. It describes forty-five conceptual functions organized into five functional groups. The functionality derived from the analysis of the content management systems is described using the vocabulary provided by the functional framework. Coverage of the concepts in the existing systems is verified. The utility of the framework is validated through the creation of a prototype that implements sufficient functionality to support a set of specific use …
Trykipedia: Collaborative Bio-Ontology Development Using Wiki Environment, Pramod Anantharam, Satya S. Sahoo, Brent Weatherly, Flora Logan, Raghava Mutharaju, Amit P. Sheth, Rick L. Tarleton
Trykipedia: Collaborative Bio-Ontology Development Using Wiki Environment, Pramod Anantharam, Satya S. Sahoo, Brent Weatherly, Flora Logan, Raghava Mutharaju, Amit P. Sheth, Rick L. Tarleton
Kno.e.sis Publications
Biomedical ontology development is an intensely collaborative process between biology experts and computer scientists. With the proliferation of ontology based approach to solve informatics problems in biological domain, there is a need for collaborative environment that is intuitive and widely accepted for modeling the ontology.
Residual-Based Estimation Of Peer And Link Lifetimes In P2p Networks, Xiaoming Wang, Zhongmei Yao, Dmitri Loguinov
Residual-Based Estimation Of Peer And Link Lifetimes In P2p Networks, Xiaoming Wang, Zhongmei Yao, Dmitri Loguinov
Computer Science Faculty Publications
Existing methods of measuring lifetimes in P2P systems usually rely on the so-called Create-BasedMethod (CBM), which divides a given observation window into two halves and samples users ldquocreatedrdquo in the first half every Delta time units until they die or the observation period ends. Despite its frequent use, this approach has no rigorous accuracy or overhead analysis in the literature. To shed more light on its performance, we first derive a model for CBM and show that small window size or large Delta may lead to highly inaccurate lifetime distributions. We then show that create-based sampling exhibits an inherent …
An Ontological Representation Of Time Series Observations On The Semantic Sensor Web, Cory Andrew Henson, Holger Neuhaus, Amit P. Sheth, Krishnaprasad Thirunarayan, Rajkumar Buyya
An Ontological Representation Of Time Series Observations On The Semantic Sensor Web, Cory Andrew Henson, Holger Neuhaus, Amit P. Sheth, Krishnaprasad Thirunarayan, Rajkumar Buyya
Kno.e.sis Publications
Time series observations are a common method of collecting sensor data. The Open Geospatial Consortium (OGC) Sensor Web Enablement (SWE) provides a standard representation for time series observations within the Observations and Measurements language, and therefore is in heavy use on the Sensor Web. By providing a common model, Observations and Measurements (O&M) facilitates syntax-level integration, but lacks the ability to facilitate semantic-level integration. This inability can cause problems with interoperability between disparate sensor networks that may have subtle variations in their sensing methods. An ontological representation of time series observations could provide a more expressive model and resolve problems …
Information Sharing And Strategic Signaling In Supply Chains, Robert J. Kauffman, Hamid Mohtadi
Information Sharing And Strategic Signaling In Supply Chains, Robert J. Kauffman, Hamid Mohtadi
Research Collection School Of Computing and Information Systems
Information sharing in procurement occurs in rich and varied industry contexts in which managerial decisions are made and organizational strategy is formulated. We explore how information sharing ought to work in procurement contexts that involve investments in inter-organizational information systems (IOS) and collaborative planning, forecasting and replenishment (CPFR) practices. How and under what circumstances does a firm that plays the role of a supply chain buyer decide to share information on key variables, such as point-of-sale consumer demand data with its supplier, up the supply chain? This is a key issue that crosses the boundary between supply chain management and …