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Articles 751 - 780 of 1060

Full-Text Articles in Numerical Analysis and Scientific Computing

Effective Music Tagging Through Advanced Statistical Modeling, Jialie Shen, Meng Wang, Shuicheng Yan, Hwee Hwa Pang, Xian-Sheng Hua Jul 2010

Effective Music Tagging Through Advanced Statistical Modeling, Jialie Shen, Meng Wang, Shuicheng Yan, Hwee Hwa Pang, Xian-Sheng Hua

Research Collection School Of Computing and Information Systems

Music information retrieval (MIR) holds great promise as a technology for managing large music archives. One of the key components of MIR that has been actively researched into is music tagging. While significant progress has been achieved, most of the existing systems still adopt a simple classification approach, and apply machine learning classifiers directly on low level acoustic features. Consequently, they suffer the shortcomings of (1) poor accuracy, (2) lack of comprehensive evaluation results and the associated analysis based on large scale datasets, and (3) incomplete content representation, arising from the lack of multimodal and temporal information integration. In this …

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Hybrid Time-Frequency Domain Analysis For Inverter-Fed Induction Motor Fault Detection, T. W. Chua, W. W. Tan, Zhaoxia Wang, C. S. Chang Jul 2010

Hybrid Time-Frequency Domain Analysis For Inverter-Fed Induction Motor Fault Detection, T. W. Chua, W. W. Tan, Zhaoxia Wang, C. S. Chang

Research Collection School Of Computing and Information Systems

The detection of faults in an induction motor is important as a part of preventive maintenance. Stator current is one of the most popular signals used for utility-supplied induction motor fault detection as a current sensor can be installed nonintrusively. In variable speeds operation, the use of an inverter to drive the induction motor introduces noise into the stator current so stator current based fault detection techniques become less reliable. This paper presents a hybrid algorithm, which combines time and frequency domain analysis, for broken rotor bar and bearing fault detection. Cluster information obtained by using Independent Component Analysis (ICA) …

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Impact Of Flow And Brand Equity In 3d Virtual Worlds, Fiona Fui-Hoon Nah, Brenda Eschenbrenner, David Dewester, So Ra Park Jul 2010

Impact Of Flow And Brand Equity In 3d Virtual Worlds, Fiona Fui-Hoon Nah, Brenda Eschenbrenner, David Dewester, So Ra Park

Research Collection School Of Computing and Information Systems

This research is a partial test of Park et al.’s (2008) model to assess the impact of flow and brand equity in 3D virtual worlds. It draws on flow theory as its main theoretical foundation to understand and empirically assess the impact of flow on brand equity and behavioral intention in 3D virtual worlds. The findings suggest that the balance of skills and challenges in 3D virtual worlds influences users’ flow experience, which in turn influences brand equity. Brand equity then increases behavioral intention. The authors also found that the impact of flow on behavioral intention in 3D virtual worlds …

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Prediction Of Protein Subcellular Localization: A Machine Learning Approach, Kyong Jin Shim Jun 2010

Prediction Of Protein Subcellular Localization: A Machine Learning Approach, Kyong Jin Shim

Research Collection School Of Computing and Information Systems

Subcellular localization is a key functional characteristic of proteins. Optimally combining available information is one of the key challenges in today's knowledge-based subcellular localization prediction approaches. This study explores machine learning approaches for the prediction of protein subcellular localization that use resources concerning Gene Ontology and secondary structures. Using the spectrum kernel for feature representation of amino acid sequences and secondary structures, we explore an SVM-based learning method that classifies six subcellular localization sites: endoplasmic reticulum, extracellular, Golgi, membrane, mitochondria, and nucleus.

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Using Hadoop And Cassandra For Taxi Data Analytics: A Feasibility Study, Alvin Jun Yong Koh, Xuan Khoa Nguyen, C. Jason Woodard Jun 2010

Using Hadoop And Cassandra For Taxi Data Analytics: A Feasibility Study, Alvin Jun Yong Koh, Xuan Khoa Nguyen, C. Jason Woodard

Research Collection School Of Computing and Information Systems

This paper reports on a preliminary study to assess the feasibility of using the Open Cirrus Cloud Computing Research testbed to provide offline and online analytical support for taxi fleet operations. In the study, we benchmarked the performance gains from distributing the offline analysis of GPS location traces over multiple virtual machines using the Apache Hadoop implementation of the MapReduce paradigm. We also explored the use of the Apache Cassandra distributed database system for online retrieval of vehicle trace data. While configuring the testbed infrastructure was straightforward, we encountered severe I/O bottlenecks in running the benchmarks due to the lack …

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Efficient Mutual Nearest Neighbor Query Processing For Moving Object Trajectories, Yunjun Gao, Baihua Zheng, Gencai Chen, Qing Li, Chun Chen, Gang Chen Jun 2010

Efficient Mutual Nearest Neighbor Query Processing For Moving Object Trajectories, Yunjun Gao, Baihua Zheng, Gencai Chen, Qing Li, Chun Chen, Gang Chen

Research Collection School Of Computing and Information Systems

Given a set D of trajectories, a query object q, and a query time extent Γ, a mutual (i.e., symmetric) nearest neighbor (MNN) query over trajectories finds from D, the set of trajectories that are among the k1 nearest neighbors (NNs) of q within Γ, and meanwhile, have q as one of their k2 NNs. This type of queries is useful in many applications such as decision making, data mining, and pattern recognition, as it considers both the proximity of the trajectories to q and the proximity of q to the trajectories. In this paper, we first formalize MNN search …

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Do Wikipedians Follow Domain Experts? A Domain-Specific Study On Wikipedia Contribution, Yi Zhang, Aixin Sun, Anwitaman Datta, Kuiyu Chang, Ee Peng Lim Jun 2010

Do Wikipedians Follow Domain Experts? A Domain-Specific Study On Wikipedia Contribution, Yi Zhang, Aixin Sun, Anwitaman Datta, Kuiyu Chang, Ee Peng Lim

Research Collection School Of Computing and Information Systems

Wikipedia is one of the most successful online knowledge bases, attracting millions of visits daily. Not surprisingly, its huge success has in turn led to immense research interest for a better understanding of the collaborative knowledge building process. In this paper, we performed a (terrorism) domain-specific case study, comparing and contrasting the knowledge evolution in Wikipedia with a knowledge base created by domain experts. Specifically, we used the Terrorism Knowledge Base (TKB) developed by experts at MIPT. We identified 409 Wikipedia articles matching TKB records, and went ahead to study them from three aspects: creation, revision, and link evolution. We …

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Stevent: Spatio-Temporal Event Model For Social Network Discovery, Hady W. Lauw, Ee Peng Lim, Hwee Hwa Pang, Teck-Tim Tan Jun 2010

Stevent: Spatio-Temporal Event Model For Social Network Discovery, Hady W. Lauw, Ee Peng Lim, Hwee Hwa Pang, Teck-Tim Tan

Research Collection School Of Computing and Information Systems

Spatio-temporal data concerning the movement of individuals over space and time contains latent information on the associations among these individuals. Sources of spatio-temporal data include usage logs of mobile and Internet technologies. This article defines a spatio-temporal event by the co-occurrences among individuals that indicate potential associations among them. Each spatio-temporal event is assigned a weight based on the precision and uniqueness of the event. By aggregating the weights of events relating two individuals, we can determine the strength of association between them. We conduct extensive experimentation to investigate both the efficacy of the proposed model as well as the …

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Efficient Processing Of Exact Top-K Queries Over Disk-Resident Sorted Lists, Hwee Hwa Pang, Xuhua Ding, Baihua Zheng Jun 2010

Efficient Processing Of Exact Top-K Queries Over Disk-Resident Sorted Lists, Hwee Hwa Pang, Xuhua Ding, Baihua Zheng

Research Collection School Of Computing and Information Systems

The top-k query is employed in a wide range of applications to generate a ranked list of data that have the highest aggregate scores over certain attributes. As the pool of attributes for selection by individual queries may be large, the data are indexed with per-attribute sorted lists, and a threshold algorithm (TA) is applied on the lists involved in each query. The TA executes in two phases--find a cut-off threshold for the top-k result scores, then evaluate all the records that could score above the threshold. In this paper, we focus on exact top-k queries that involve monotonic linear …

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Player Performance Prediction In Massively Multiplayer Online Role-Playing Games (Mmorpgs), Kyong Jin Shim, Richa Sharan, Jaideep Srivastava Jun 2010

Player Performance Prediction In Massively Multiplayer Online Role-Playing Games (Mmorpgs), Kyong Jin Shim, Richa Sharan, Jaideep Srivastava

Research Collection School Of Computing and Information Systems

In this study, we propose a comprehensive performance management tool for measuring and reporting operational activities of game players. This study uses performance data of game players in EverQuest II, a popular MMORPG developed by Sony Online Entertainment, to build performance prediction models forgame players. The prediction models provide a projection of player’s future performance based on his past performance, which is expected to be a useful addition to existing player performance monitoring tools. First, we show that variations of PECOTA [2] and MARCEL [3], two most popular baseball home run prediction methods, can be used for game player performance …

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Z-Sky: An Efficient Skyline Query Processing Framework Based On Z-Order, Ken C. K. Lee, Wang-Chien Lee, Baihua Zheng, Huajing Li, Yuan Tian Jun 2010

Z-Sky: An Efficient Skyline Query Processing Framework Based On Z-Order, Ken C. K. Lee, Wang-Chien Lee, Baihua Zheng, Huajing Li, Yuan Tian

Research Collection School Of Computing and Information Systems

Given a set of data points in a multidimensional space, a skyline query retrieves those data points that are not dominated by any other point in the same dataset. Observing that the properties of Z-order space filling curves (or Z-order curves) perfectly match with the dominance relationships among data points in a geometrical data space, we, in this paper, develop and present a novel and efficient processing framework to evaluate skyline queries and their variants, and to support skyline result updates based on Z-order curves. This framework consists of ZBtree, i.e., an index structure to organize a source dataset and …

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Visualizing And Exploring Evolving Information Networks In Wikipedia, Ee Peng Lim, Agus Trisnajaya Kwee, Nelman Lubis Ibrahim, Aixin Sun, Anwitaman Datta, Kuiyu Chang, Maureen Maureen Jun 2010

Visualizing And Exploring Evolving Information Networks In Wikipedia, Ee Peng Lim, Agus Trisnajaya Kwee, Nelman Lubis Ibrahim, Aixin Sun, Anwitaman Datta, Kuiyu Chang, Maureen Maureen

Research Collection School Of Computing and Information Systems

Information networks in Wikipedia evolve as users collaboratively edit articles that embed the networks. These information networks represent both the structure and content of community’s knowledge and the networks evolve as the knowledge gets updated. By observing the networks evolve and finding their evolving patterns, one can gain higher order knowledge about the networks and conduct longitudinal network analysis to detect events and summarize trends. In this paper, we present SSNetViz+, a visual analytic tool to support visualization and exploration of Wikipedia’s information networks. SSNetViz+ supports time-based network browsing, content browsing and search. Using a terrorism information network as an …

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Two-View Transductive Support Vector Machines, Guangxia Li, Steven C. H. Hoi, Kuiyu Chang May 2010

Two-View Transductive Support Vector Machines, Guangxia Li, Steven C. H. Hoi, Kuiyu Chang

Research Collection School Of Computing and Information Systems

Obtaining high-quality and up-to-date labeled data can be difficult in many real-world machine learning applications, especially for Internet classification tasks like review spam detection, which changes at a very brisk pace. For some problems, there may exist multiple perspectives, so called views, of each data sample. For example, in text classification, the typical view contains a large number of raw content features such as term frequency, while a second view may contain a small but highly-informative number of domain specific features. We thus propose a novel two-view transductive SVM that takes advantage of both the abundant amount of unlabeled data …

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Optimal Matching Between Spatial Datasets Under Capacity Constraints, Hou U Leong, Kyriakos Mouratidis, Man Lung Yiu, Nikos Mamoulis Apr 2010

Optimal Matching Between Spatial Datasets Under Capacity Constraints, Hou U Leong, Kyriakos Mouratidis, Man Lung Yiu, Nikos Mamoulis

Research Collection School Of Computing and Information Systems

Consider a set of customers (e.g., WiFi receivers) and a set of service providers (e.g., wireless access points), where each provider has a capacity and the quality of service offered to its customers is anti-proportional to their distance. The capacity constrained assignment (CCA) is a matching between the two sets such that (i) each customer is assigned to at most one provider, (ii) every provider serves no more customers than its capacity, (iii) the maximum possible number of customers are served, and (iv) the sum of Euclidean distances within the assigned provider-customer pairs is minimized. Although max-flow algorithms are applicable …

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What Is Twitter, A Social Network Or A News Media?, Haewoon Kwak, Changhyun Lee, Hosung: Moon Park Apr 2010

What Is Twitter, A Social Network Or A News Media?, Haewoon Kwak, Changhyun Lee, Hosung: Moon Park

Research Collection School Of Computing and Information Systems

Twitter, a microblogging service less than three years old, commands more than 41 million users as of July 2009 and is growing fast. Twitter users tweet about any topic within the 140-character limit and follow others to receive their tweets. The goal of this paper is to study the topological characteristics of Twitter and its power as a new medium of information sharing.We have crawled the entire Twitter site and obtained 41.7 million user profiles, 1.47 billion social relations, 4,262 trending topics, and 106 million tweets. In its follower-following topology analysis we have found a non-power-law follower distribution, a short …

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Policy-Driven Distributed And Collaborative Demand Response In Multi-Domain Commercial Buildings, Archan Misra, Henning Schulzrinne Apr 2010

Policy-Driven Distributed And Collaborative Demand Response In Multi-Domain Commercial Buildings, Archan Misra, Henning Schulzrinne

Research Collection School Of Computing and Information Systems

Enabling a sophisticated Demand Response (DR) framework, whereby individual consumers adapt their electricity consumption in response to price variations, is a major objective of the emerging Smart Grid. We first point out why the current model, of EMS-based centralized control of a static repository of high load appliances, is inappropriate for supporting DR in future commercial buildings and campuses, where the consuming appliances are controlled by multiple users. To enable DR in such multi-domain environments, we envision a more collaborative and autonomous model, where a large set of heterogeneous smart electrical devices autonomously self-organize and negotiate their collective DR. Enabling …

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Finding Influentials Based On The Temporal Order Of Information Adoption In Twitter, Changhyun Lee, Haewoon Kwak, Hosung Park, Sue Moon Apr 2010

Finding Influentials Based On The Temporal Order Of Information Adoption In Twitter, Changhyun Lee, Haewoon Kwak, Hosung Park, Sue Moon

Research Collection School Of Computing and Information Systems

Twitter offers an explicit mechanism to facilitate information diffusion and has emerged as a new medium for communication. Many approaches to find influentials have been proposed, but they do not consider the temporal order of information adoption. In this work, we propose a novel method to find influentials by considering both the link structure and the temporal order of information adoption in Twitter. Our method finds distinct influentials who are not discovered by other methods.

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Continuous Spatial Assignment Of Moving Users, Hou U Leong, Kyriakos Mouratidis, Nikos Mamoulis Apr 2010

Continuous Spatial Assignment Of Moving Users, Hou U Leong, Kyriakos Mouratidis, Nikos Mamoulis

Research Collection School Of Computing and Information Systems

Consider a set of servers and a set of users, where each server has a coverage region (i.e., an area of service) and a capacity (i.e., a maximum number of users it can serve). Our task is to assign every user to one server subject to the coverage and capacity constraints. To offer the highest quality of service, we wish to minimize the average distance between users and their assigned server. This is an instance of a well-studied problem in operations research, termed optimal assignment. Even though there exist several solutions for the static case (where user locations are fixed), …

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Data Mining Based Predictive Models For Overall Health Indices, Ridhima Rajkumar, Kyong Jin Shim, Jaideep Srivastava Apr 2010

Data Mining Based Predictive Models For Overall Health Indices, Ridhima Rajkumar, Kyong Jin Shim, Jaideep Srivastava

Research Collection School Of Computing and Information Systems

In this study, we infer health care indices of individuals using their pharmacy medical and prescription claims. Specifically, we focus on the widely used Charlson Index. We use data mining techniques to formulate the problem of classifying Charlson Index (CI) and build predictive models to predict individual health index score. First, we present comparative analyses of several classification algorithms. Second, our study shows that certain ensemble algorithms lead to higher prediction accuracy in comparison to base algorithms. Third, we introduce cost-sensitive learning to the classification algorithms and show that the inclusion of cost-sensitive learning leads to improved prediction accuracy. The …

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Algorithms For Constrained K-Nearest Neighbor Queries Over Moving Object Trajectories, Yunjun Gao, Baihua Zheng, Gencai Chen, Qing Li, Chun Chen Apr 2010

Algorithms For Constrained K-Nearest Neighbor Queries Over Moving Object Trajectories, Yunjun Gao, Baihua Zheng, Gencai Chen, Qing Li, Chun Chen

Research Collection School Of Computing and Information Systems

An important query for spatio-temporal databases is to find nearest trajectories of moving objects. Existing work on this topic focuses on the closest trajectories in the whole data space. In this paper, we introduce and solve constrained k-nearest neighbor (CkNN) queries and historical continuous CkNN (HCCkNN) queries on R-tree-like structures storing historical information about moving object trajectories. Given a trajectory set D, a query object (point or trajectory) q, a temporal extent T, and a constrained region CR, (i) a CkNN query over trajectories retrieves from D within T, the k (≥ 1) trajectories that lie closest to q and …

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Mining Diversity On Networks, Lu Liu, Feida Zhu, Chen Chen, Xifeng Yan, Jiawei Han, Philip Yu, Shiqiang Yang Apr 2010

Mining Diversity On Networks, Lu Liu, Feida Zhu, Chen Chen, Xifeng Yan, Jiawei Han, Philip Yu, Shiqiang Yang

Research Collection School Of Computing and Information Systems

Despite the recent emergence of many large-scale networks in different application domains, an important measure that captures a participant’s diversity in the network has been largely neglected in previous studies. Namely, diversity characterizes how diverse a given node connects with its peers. In this paper, we give a comprehensive study of this concept. We first lay out two criteria that capture the semantic meaning of diversity, and then propose a compliant definition which is simple enough to embed the idea. An efficient top-k diversity ranking algorithm is developed for computation on dynamic networks. Experiments on both synthetic and real datasets …

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Do You Trust To Get Trust? A Study Of Trust Reciprocity Behaviors And Reciprocal Trust Prediction, Viet-An Nguyen, Ee Peng Lim, Hwee Hoon Tan, Jing Jiang, Aixin Sun Apr 2010

Do You Trust To Get Trust? A Study Of Trust Reciprocity Behaviors And Reciprocal Trust Prediction, Viet-An Nguyen, Ee Peng Lim, Hwee Hoon Tan, Jing Jiang, Aixin Sun

Research Collection School Of Computing and Information Systems

Trust reciprocity, a special form of link reciprocity, exists in many networks of trust among users. In this paper, we seek to determine the extent to which reciprocity exists in a trust network and develop quantitative models for measuring reciprocity and reciprocity related behaviors. We identify several reciprocity behaviors and their respective measures. These behavior measures can be employed for predicting if a trustee will return trust to her trustor given that the latter initiates a trust link earlier. We develop for this reciprocal trust prediction task a number of ranking method and classification methods, and evaluated them on an …

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Information Search Patterns In E-Commerce Product Comparison Services, Fiona Fui-Hoon Nah, Weiyin Hong, Liqiang Chen, Hong-Hee Lee Apr 2010

Information Search Patterns In E-Commerce Product Comparison Services, Fiona Fui-Hoon Nah, Weiyin Hong, Liqiang Chen, Hong-Hee Lee

Research Collection School Of Computing and Information Systems

To facilitate product selection and purchase decisions on e-commerce Web sites, the presentation of product information is very important. In this research, the authors study how disposition styles influence users’ search patterns in product comparison services of e-commerce Web sites. The results show that people use relatively more feature paths and less product paths in vertical disposition style than horizontal disposition style. The findings also indicate that there are relatively more feature paths and less product paths in the first half than second half of the information search paths. This is consistent with Gensch’s two-stage choice model which suggests that …

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Symphony: A Platform For Search-Driven Applications, John C. Shafer, Rakesh Agrawal, Hady W. Lauw Mar 2010

Symphony: A Platform For 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 Bing infrastructure. While Symphony naturally makes use of the customization capabilities exposed by Bing, its distinguishing feature is the capability it provides to the application creator to combine their proprietary data and domain expertise with content obtained from Bing. They can also integrate specialized data obtained from web services to enhance the richness …

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Top-K Aggregation Queries Over Large Networks, Xifeng Yan, Bin He, Feida Zhu, Jiawei Han Mar 2010

Top-K Aggregation Queries Over Large Networks, Xifeng Yan, Bin He, Feida Zhu, Jiawei Han

Research Collection School Of Computing and Information Systems

Searching and mining large graphs today is critical to a variety of application domains, ranging from personalized recommendation in social networks, to searches for functional associations in biological pathways. In these domains, there is a need to perform aggregation operations on large-scale networks. Unfortunately the existing implementation of aggregation operations on relational databases does not guarantee superior performance in network space, especially when it involves edge traversals and joins of gigantic tables. In this paper, we investigate the neighborhood aggregation queries: Find nodes that have top-k highest aggregate values over their h-hop neighbors. While these basic queries are common in …

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Local Coordination Under Bounded Rationality: Coase Meets Simon, Finds Hayek, C. Jason Woodard Mar 2010

Local Coordination Under Bounded Rationality: Coase Meets Simon, Finds Hayek, C. Jason Woodard

Research Collection School Of Computing and Information Systems

This paper explores strategic behavior in a network of firms using an agent-based model. The model exhibits a tension between economic efficiency and the stability of the network in the face of incentives to change its configuration. This tension is to be expected because the conditions of the Coase theorem are violated: the boundedly rational firms in the model lack the ability to discover efficient network configurations or achieve them through collective action. In computational experiments, as predicted by theory, firms frequently became locked into inefficient outcomes or endless cycles of mutual frustration. However, simple institutional innovations such as property …

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Fuzzy Matching Of Web Queries To Structured Data, Tao Cheng, Hady W. Lauw, Stelios Paparizos Mar 2010

Fuzzy Matching Of Web Queries To Structured Data, Tao Cheng, Hady W. Lauw, Stelios Paparizos

Research Collection School Of Computing and Information Systems

Recognizing the alternative ways people use to reference an entity, is important for many Web applications that query structured data. In such applications, there is often a mismatch between how content creators describe entities and how different users try to retrieve them. In this paper, we consider the problem of determining whether a candidate query approximately matches with an entity. We propose an off-line, data-driven, bottom-up approach that mines query logs for instances where Web content creators and Web users apply a variety of strings to refer to the same Web pages. This way, given a set of strings that …

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Homophily In The Digital World: A Livejournal Case Study, Hady W. Lauw, John C. Shafer, Rakesh Agrawal, Alexandros Ntoulas Mar 2010

Homophily In The Digital World: A Livejournal Case Study, Hady W. Lauw, John C. Shafer, Rakesh Agrawal, Alexandros Ntoulas

Research Collection School Of Computing and Information Systems

Are two users more likely to be friends if they share common interests? Are two users more likely to share common interests if they're friends? The authors study the phenomenon of homophily in the digital world by answering these central questions. Unlike the physical world, the digital world doesn't impose any geographic or organizational constraints on friendships. So, although online friends might share common interests, a priori there's no reason to believe that two users with common interests are more likely to be friends. Using data from LiveJournal, the authors show that the answer to both questions is yes.

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Preference Queries In Large Multi-Cost Transportation Networks, Kyriakos Mouratidis, Yimin Lin, Man Lung Yiu Mar 2010

Preference Queries In Large Multi-Cost Transportation Networks, Kyriakos Mouratidis, Yimin Lin, Man Lung Yiu

Research Collection School Of Computing and Information Systems

Research on spatial network databases has so far considered that there is a single cost value associated with each road segment of the network. In most real-world situations, however, there may exist multiple cost types involved in transportation decision making. For example, the different costs of a road segment could be its Euclidean length, the driving time, the walking time, possible toll fee, etc. The relative significance of these cost types may vary from user to user. In this paper we consider such multi-cost transportation networks (MCN), where each edge (road segment) is associated with multiple cost values. We formulate …

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Efficient Verification Of Shortest Path Search Via Authenticated Hints, Man Lung Yiu, Yimin Lin, Kyriakos Mouratidis Mar 2010

Efficient Verification Of Shortest Path Search Via Authenticated Hints, Man Lung Yiu, Yimin Lin, Kyriakos Mouratidis

Research Collection School Of Computing and Information Systems

Shortest path search in transportation networks is unarguably one of the most important online search services nowadays (e.g., Google Maps, MapQuest, etc), with applications spanning logistics, spatial optimization, or everyday driving decisions. Often times, the owner of the road network data (e.g., a transport authority) provides its database to third-party query services, which are responsible for answering shortest path queries posed by their clients. The issue arising here is that a query service might be returning sub-optimal paths either purposely (in order to serve its own purposes like computational savings or commercial reasons) or because it has been compromised by …

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