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Full-Text Articles in Entire DC Network
Electric Elves: What Went Wrong And Why, Milind Tambe, Emma Bowring, Jonathan Pearce, Pradeep Reddy Varakantham, Paul Scerri, David V. Pynadath
Electric Elves: What Went Wrong And Why, Milind Tambe, Emma Bowring, Jonathan Pearce, Pradeep Reddy Varakantham, Paul Scerri, David V. Pynadath
Research Collection School Of Computing and Information Systems
Software personal assistants continue to be a topic of significant research interest. This article outlines some of the important lessons learned from a successfully-deployed team of personal assistant agents (Electric Elves) in an office environment. In the Electric Elves project, a team of almost a dozen personal assistant agents were continually active for seven months. Each elf (agent) represented one person and assisted in daily activities in an actual office environment. This project led to several important observations about privacy, adjustable autonomy, and social norms in office environments. In addition to outlining some of the key lessons learned we outline …
Wikinetviz: Visualizing Friends And Adversaries In Implicit Social Networks, Minh-Tam Le, Hoang-Vu Dang, Ee Peng Lim, Anwitaman Datta
Wikinetviz: Visualizing Friends And Adversaries In Implicit Social Networks, Minh-Tam Le, Hoang-Vu Dang, Ee Peng Lim, Anwitaman Datta
Research Collection School Of Computing and Information Systems
When multiple users with diverse backgrounds and beliefs edit Wikipedia together, disputes often arise due to disagreements among the users. In this paper, we introduce a novel visualization tool known as WikiNetViz to visualize and analyze disputes among users in a dispute-induced social network. WikiNetViz is designed to quantify the degree of dispute between a pair of users using the article history. Each user (and article) is also assigned a controversy score by our proposed controversy rank model so as to measure the degree of controversy of a user (and an article) by the amount of disputes between the user …
Visual Analytics For Supporting Entity Relationship Discovery On Text Data, Hanbo Dai, Ee Peng Lim, Hady W. Lauw, Hwee Hwa Pang
Visual Analytics For Supporting Entity Relationship Discovery On Text Data, Hanbo Dai, Ee Peng Lim, Hady W. Lauw, Hwee Hwa Pang
Research Collection School Of Computing and Information Systems
To conduct content analysis over text data, one may look out for important named objects and entities that refer to real world instances, synthesizing them into knowledge relevant to a given information seeking task. In this paper, we introduce a visual analytics tool called ER-Explorer to support such an analysis task. ER-Explorer consists of a data model known as TUBE and a set of data manipulation operations specially designed for examining entities and relationships in text. As part of TUBE, a set of interestingness measures is defined to help exploring entities and their relationships. We illustrate the use of ER-Explorer …
Information-Theory Based Optimal Location Management Schemes For Integrated Multi-System Wireless Networks, Archan Misra, Abhishek Roy, Sajal K. Das
Information-Theory Based Optimal Location Management Schemes For Integrated Multi-System Wireless Networks, Archan Misra, Abhishek Roy, Sajal K. Das
Research Collection School Of Computing and Information Systems
In a multisystem environment where a mobile node can utilize multiple interfaces and simultaneously connect to multiple providers, new opportunities exist for efficient location management strategies spanning heterogeneous cellular wireless networks. In this paper, an integrated framework is developed for location management in such a multi-system, fourth generation (4 G) wireless networks. This information-theoretic framework allows each individual sub-system to operate fairly independently, and does not require the knowledge of individual sub-network topologies. An efficient location management in such a loosely coupled network is designed by having a mobile node view its movement as a vector-valued sequence, and then transmit …
Localized Minimum-Latency Broadcasting In Multi-Radio Multi-Rate Wireless Mesh Networks, Junaid Qadir, Chun Tung Chou, Archan Misra, Joo Ghee Lim
Localized Minimum-Latency Broadcasting In Multi-Radio Multi-Rate Wireless Mesh Networks, Junaid Qadir, Chun Tung Chou, Archan Misra, Joo Ghee Lim
Research Collection School Of Computing and Information Systems
We address the problem of minimizing the worst-case broadcast delay in ldquomulti-radio multi-channel multi-rate wireless mesh networksrdquo (MR2-MC WMN) in a distributed and localized fashion. Efficient broadcasting in such networks is especially challenging due to the desirability of exploiting the ldquowireless broadcast advantagerdquo (WBA), the interface-diversity, the channel-diversity and the rate-diversity offered by these networks. We propose a framework that calculates a set of forwarding nodes and transmission rate at these forwarding nodes irrespective of the broadcast source. Thereafter, a forwarding tree is constructed taking into consideration the source of broadcast. Our broadcasting algorithms are distributed and utilize locally available …
Semi-Supervised Distance Metric Learning For Collaborative Image Retrieval, Steven Hoi, Wei Liu, Shih-Fu Chang
Semi-Supervised Distance Metric Learning For Collaborative Image Retrieval, Steven Hoi, Wei Liu, Shih-Fu Chang
Research Collection School Of Computing and Information Systems
Typical content-based image retrieval (CBIR) solutions with regular Euclidean metric usually cannot achieve satisfactory performance due to the semantic gap challenge. Hence, relevance feedback has been adopted as a promising approach to improve the search performance. In this paper, we propose a novel idea of learning with historical relevance feedback log data, and adopt a new paradigm called “Collaborative Image Retrieval” (CIR). To effectively explore the log data, we propose a novel semi-supervised distance metric learning technique, called “Laplacian Regularized Metric Learning” (LRML), for learning robust distance metrics for CIR. Different from previous methods, the proposed LRML method integrates both …
Architectural Control Points, C. Jason Woodard
Architectural Control Points, C. Jason Woodard
Research Collection School Of Computing and Information Systems
System designers and technology strategists have long recognized the concept of an architectural control point as a way to identify parts of a system that have particular strategic importance. Despite the vast body of work on system architecture in the engineering design literature, however, few authors have attempted to define architectural control points or study them systematically. Moreover, some industry participants have questioned whether architectural control is still a valuable or achievable goal in an era of increasingly open standards. This paper offers tentative definitions of architectural control, architectural control points, and architectural strategy. In a longer version of the …
Verifying Completeness Of Relational Query Answers From Online Servers, Hwee Hwa Pang, Kian-Lee Tan
Verifying Completeness Of Relational Query Answers From Online Servers, Hwee Hwa Pang, Kian-Lee Tan
Research Collection School Of Computing and Information Systems
The number of successful attacks on the Internet shows that it is very difficult to guarantee the security of online servers over extended periods of time. A breached server that is not detected in time may return incorrect query answers to users. In this article, we introduce authentication schemes for users to verify that their query answers from an online server are complete (i.e., no qualifying tuples are omitted) and authentic (i.e., all the result values are legitimate). We introduce a scheme that supports range selection, projection as well as primary key-foreign key join queries on relational databases. We also …
A Formal Model Of Semantic Web Service Ontology (Wsmo) Execution, Hai H. Wang, Nick Gibbins, Terry R. Payne, Ahmed Saleh, Jun Sun
A Formal Model Of Semantic Web Service Ontology (Wsmo) Execution, Hai H. Wang, Nick Gibbins, Terry R. Payne, Ahmed Saleh, Jun Sun
Research Collection School Of Computing and Information Systems
Semantic Web services have been one of the most significant research areas within the semantic Web vision, and have been recognized as a promising technology that exhibits huge commercial potential. Current semantic Web service research focuses on defining models and languages for the semantic markup of all relevant aspects of services, which are accessible through a Web service interface. The Web service modelling ontology (WSMO) is one of the most significant semantic Web service framework proposed to date. To support the standardization and tool support of WSMO, a formal semantics of the language is highly desirable. As there are a …
K-Sketch: A 'Kinetic' Sketch Pad For Novice Animators, Richard C. Davis, Brien Colwell, James A. Landay
K-Sketch: A 'Kinetic' Sketch Pad For Novice Animators, Richard C. Davis, Brien Colwell, James A. Landay
Research Collection School Of Computing and Information Systems
Because most animation tools are complex and timeconsuming to learn and use, most animations today are created by experts. To help novices create a wide range of animations quickly, we have developed a general-purpos informal, 2D animation sketching system called K-Sketch. Field studies investigating the needs of animatorsnd would-be animators helped us collect a library of usage scenarios for our tool. A novel optimization technique enabled us to design an interface that is simultaneously fast, simple, and powerful. The result is a pen-based system that relies on users’ intuitive sense of space and time while still supporting a wide range …
Efficient Optimistic Fair Exchange Secure In The Multi-User Setting And Chosen-Key Model Without Random Oracles, Qiong Huang, Guomin Yang, Duncan S. Wong, Willy Susilo
Efficient Optimistic Fair Exchange Secure In The Multi-User Setting And Chosen-Key Model Without Random Oracles, Qiong Huang, Guomin Yang, Duncan S. Wong, Willy Susilo
Research Collection School Of Computing and Information Systems
Optimistic fair exchange is a kind of protocols to solve the problem of fair exchange between two parties. Almost all the previous work on this topic are provably secure only in the random oracle model. In PKC 2007, Dodis et al. considered optimistic fair exchange in a multi-user setting, and showed that the security of an optimistic fair exchange in a single-user setting may no longer be secure in a multi-user setting. Besides, they also proposed one and reviewed several previous construction paradigms and showed that they are secure in the multi-user setting. However, their proofs are either in the …
Benefiting From Customer And Competitor Knowledge: A Market-Based Approach To Organisational Learning, Siu Loon Hoe
Benefiting From Customer And Competitor Knowledge: A Market-Based Approach To Organisational Learning, Siu Loon Hoe
Research Collection School Of Computing and Information Systems
PurposeThe purpose of this paper is to review the organizational learning, market orientation and learning orientation concepts, highlight the importance of market knowledge to organizational learning and recommend ways in adopting a market‐based approach to organizational learning.Design/methodology/approachThe extant organizational learning and market orientation literature was reviewed, and the salient points on how adopting a market‐based approach to organizational learning promotes competitive advantage are discussed.FindingsOrganizational behavior scholars have devoted a lot attention on the factors and conditions affecting organizational learning. The end outcome, of course, is to improve organizational performance. Marketing scholars, on the other, focused on the effect of market …
E-Government Implementation: A Macro Analysis Of Singapore's E-Government Initiatives, Calvin M.L. Chan, Yi Meng Lau, Shan L. Pan
E-Government Implementation: A Macro Analysis Of Singapore's E-Government Initiatives, Calvin M.L. Chan, Yi Meng Lau, Shan L. Pan
Research Collection School Of Computing and Information Systems
This paper offers a macro perspective of the various activities involved in the implementation of e-government through an interpretive analysis of the various e-government-related initiatives undertaken by the Singapore Government. The analysis lead to the identification of four main components in the implementation of e-government, namely (i) information content, (ii) ICT infrastructure, (iii) e-government infostructure, and (iv) e-government promotion. These four components were then conceptually integrated into the e-Government Implementation Framework. This paper suggests that this framework can either be used as a descriptive tool to organize and coordinate various e-government initiatives, or be used as a prescriptive structure to …
Rate-Diversity And Resource-Aware Broadcast And Multicast In Multi-Rate Wireless Mesh Networks, Bao Hua Liu, Chun Tung Chou, Archan Misra, Sanjay Jha
Rate-Diversity And Resource-Aware Broadcast And Multicast In Multi-Rate Wireless Mesh Networks, Bao Hua Liu, Chun Tung Chou, Archan Misra, Sanjay Jha
Research Collection School Of Computing and Information Systems
This paper focuses on the problem of increasing the traffic capacity (volume of admissible traffic) of broadcast and multicast flows in a wireless mesh network (WMN). We study and suggest routing strategies where the process of constructing the forwarding tree considers three distinct features: (a) the ability of individual mesh nodes to perform link-layer broadcasts at multiple rates, (b) the wireless broadcast advantage, whereby a single broadcast transmission covers multiple neighboring receivers and (c) the residual transmission capacity at a WMN node, subject to intereference-based constraints from existing traffic flows in its neighborhood. Our metric of interest is the total …
Multimodal News Story Clustering With Pairwise Visual Near-Duplicate Constraint, Xiao Wu, Chong-Wah Ngo, Alexander G. Hauptmann
Multimodal News Story Clustering With Pairwise Visual Near-Duplicate Constraint, Xiao Wu, Chong-Wah Ngo, Alexander G. Hauptmann
Research Collection School Of Computing and Information Systems
Story clustering is a critical step for news retrieval, topic mining, and summarization. Nonetheless, the task remains highly challenging owing to the fact that news topics exhibit clusters of varying densities, shapes, and sizes. Traditional algorithms are found to be ineffective in mining these types of clusters. This paper offers a new perspective by exploring the pairwise visual cues deriving from near-duplicate keyframes (NDK) for constraint-based clustering. We propose a constraint-driven co-clustering algorithm (CCC), which utilizes the near-duplicate constraints built on top of text, to mine topic-related stories and the outliers. With CCC, the duality between stories and their underlying …
Perceptions Becoming Reality: Bridging The Market Knowledge Gap, Siu Loon Hoe
Perceptions Becoming Reality: Bridging The Market Knowledge Gap, Siu Loon Hoe
Research Collection School Of Computing and Information Systems
PurposeOrganizations constantly strive to learn about new market trends and ideas to stay ahead of the game. However, with an increased demand of market knowledge, how does the organization motivate employees to constantly acquire and disseminate market knowledge? The purpose of this paper is to highlight the perceived importance of market knowledge in promoting continuous employee acquisition and dissemination of customer and competitor knowledge.Design/methodology/approachThe perceived importance of market knowledge concept is highlighted and discussed.FindingsThe paper offers a view on how management could address the increased demand for market knowledge and how the development and learning team could provide further support …
Integrating Temporal Difference Methods And Self‐Organizing Neural Networks For Reinforcement Learning With Delayed Evaluative Feedback, Ah-Hwee Tan, Ning Lu, Dan Xiao
Integrating Temporal Difference Methods And Self‐Organizing Neural Networks For Reinforcement Learning With Delayed Evaluative Feedback, Ah-Hwee Tan, Ning Lu, Dan Xiao
Research Collection School Of Computing and Information Systems
This paper presents a neural architecture for learning category nodes encoding mappings across multimodal patterns involving sensory inputs, actions, and rewards. By integrating adaptive resonance theory (ART) and temporal difference (TD) methods, the proposed neural model, called TD fusion architecture for learning, cognition, and navigation (TD-FALCON), enables an autonomous agent to adapt and function in a dynamic environment with immediate as well as delayed evaluative feedback (reinforcement) signals. TD-FALCON learns the value functions of the state-action space estimated through on-policy and off-policy TD learning methods, specifically state-action-reward-state-action (SARSA) and Q-learning. The learned value functions are then used to determine the …
On Ranking Controversies In Wikipedia: Models And Evaluation, Ba-Quy Vuong, Ee Peng Lim, Aixin Sun, Minh-Tam Le, Hady Wirawan Lauw, Kuiyu Chang
On Ranking Controversies In Wikipedia: Models And Evaluation, Ba-Quy Vuong, Ee Peng Lim, Aixin Sun, Minh-Tam Le, Hady Wirawan Lauw, Kuiyu Chang
Research Collection School Of Computing and Information Systems
Wikipedia 1 is a very large and successful Web 2.0 example. As the number of Wikipedia articles and contributors grows at a very fast pace, there are also increasing disputes occurring among the contributors. Disputes often happen in articles with controversial content. They also occur frequently among contributors who are "aggressive" or controversial in their personalities. In this paper, we aim to identify controversial articles in Wikipedia. We propose three models, namely the Basic model and two Controversy Rank (CR) models. These models draw clues from collaboration and edit history instead of interpreting the actual articles or edited content. While …
Multi-Echelon Repairable Item Inventory System With Limited Repair Capacity Under Nonstationary Demands, Hoong Chuin Lau, Huawei Song
Multi-Echelon Repairable Item Inventory System With Limited Repair Capacity Under Nonstationary Demands, Hoong Chuin Lau, Huawei Song
Research Collection School Of Computing and Information Systems
Classical multi-echelon repairable item inventory models are based either on steady-state analysis or infinite repair capacity, which may not work well in situations when the demand is nonstationary, or repair capacity is limited. In this paper, we propose an analytical model for evaluating system performance that works well under limited repair capacity and nonstationary demands. Following the METRIC methodology, we then develop an optimisation algorithm to solve the corrective maintenance problem in military logistics. Experimental results show that our approach yields good solutions efficiently. This work has also resulted in a software that has been field-tested by a military organisation.
Benford And Your Taxes, Manoj Thulasidas
Benford And Your Taxes, Manoj Thulasidas
Research Collection School Of Computing and Information Systems
Nothing is certain but death and taxes, they say. On the death front, we are making some inroads with all our medical marvels, at least in postponing it if not actually avoiding it. But when it comes to taxes, we have no defense other than a bit of creativity in our tax returns.
A Growth-Theoretic Empirical Analysis Of Simultaneity In Cross-National E-Commerce Development, Shu-Chun Ho, Robert J. Kauffman, Ting-Peng Liang
A Growth-Theoretic Empirical Analysis Of Simultaneity In Cross-National E-Commerce Development, Shu-Chun Ho, Robert J. Kauffman, Ting-Peng Liang
Research Collection School Of Computing and Information Systems
The emergence of information and communication technologies infrastructure has transformed the global economy. The development of information technology infrastructure is limited to some developed countries though. This research explores the role of information technology infrastructure in B2C e-commerce growth at the country-level from the perspective of growth theory in economics. We propose a hybrid exogenous and endogenous growth model to explain e-commerce growth. We estimate a panel data model that incorporates the direct effects of e-commerce infrastructure and other key explanatory variables. We further specify a simultaneous effects model that permits the analysis of reverse causality in the association between …
Face Annotation Using Transductive Kernel Fisher Discriminant, Jianke Zhu, Steven C. H. Hoi, Michael R. Lyu
Face Annotation Using Transductive Kernel Fisher Discriminant, Jianke Zhu, Steven C. H. Hoi, Michael R. Lyu
Research Collection School Of Computing and Information Systems
Face annotation in images and videos enjoys many potential applications in multimedia information retrieval. Face annotation usually requires many training data labeled by hand in order to build effective classifiers. This is particularly challenging when annotating faces on large-scale collections of media data, in which huge labeling efforts would be very expensive. As a result, traditional supervised face annotation methods often suffer from insufficient training data. To attack this challenge, in this paper, we propose a novel Transductive Kernel Fisher Discriminant (TKFD) scheme for face annotation, which outperforms traditional supervised annotation methods with few training data. The main idea of …
Factors Affecting The Information Quality Of Personal Web Portfolios, P. Katerattanakul, Keng Siau
Factors Affecting The Information Quality Of Personal Web Portfolios, P. Katerattanakul, Keng Siau
Research Collection School Of Computing and Information Systems
Personal Web portfolios have become a popular information source and an effective method for individuals to present themselves to others in cyberspace. Thus, the quality of personal Web portfolios is critical and affects the perception that others have of the individuals. But how do we measure quality of personal Web portfolios? What are the important factors affecting quality of personal Web portfolios? This study presents the development of an instrument measuring factors affecting information quality of personal Web portfolios. The proposed instrument, based on the Information Quality framework, was refined and validated to assess its construct validity, convergent validity, and …
Private Query On Encrypted Data In Multi-User Setting, Feng Bao, Robert H. Deng, Xuhua Ding, Yanjiang Yang
Private Query On Encrypted Data In Multi-User Setting, Feng Bao, Robert H. Deng, Xuhua Ding, Yanjiang Yang
Research Collection School Of Computing and Information Systems
Searchable encryption schemes allow users to perform keyword based searches on an encrypted database. Almost all existing such schemes only consider the scenario where a single user acts as both the data owner and the querier. However, most databases in practice do not just serve one user; instead, they support search and write operations by multiple users. In this paper, we systematically study searchable encryption in a practical multi-user setting. Our results include a set of security notions for multi-user searchable encryption as well as a construction which is provably secure under the newly introduced security notions.
The Oil Drilling Model And Iterative Deepening Genetic Annealing Algorithm For The Traveling Salesman Problem, Hoong Chuin Lau, Fei Xiao
The Oil Drilling Model And Iterative Deepening Genetic Annealing Algorithm For The Traveling Salesman Problem, Hoong Chuin Lau, Fei Xiao
Research Collection School Of Computing and Information Systems
In this work, we liken the solving of combinatorial optimization problems under a prescribed computational budget as hunting for oil in an unexplored ground. Using this generic model, we instantiate an iterative deepening genetic annealing (IDGA) algorithm, which is a variant of memetic algorithms. Computational results on the traveling salesman problem show that IDGA is more effective than standard genetic algorithms or simulated annealing algorithms or a straightforward hybrid of them. Our model is readily applicable to solve other combinatorial optimization problems.
Collective Outsourcing To Market (Com): A Market-Based Framework For Information Supply Chain Outsourcing, Fang Fang, Zhiling Guo, Andrew B. Whinston
Collective Outsourcing To Market (Com): A Market-Based Framework For Information Supply Chain Outsourcing, Fang Fang, Zhiling Guo, Andrew B. Whinston
Research Collection School Of Computing and Information Systems
This paper discusses the importance of and a solution to separating the information flow from the physical product flow in a supply chain. Motivated by the inefficient demand forecast caused by information asymmetry and lack of an incentive among supply chain partners to share valuable information, we propose a radically new framework called collective outsourcing to market (COM) to address many information supply chain design challenges. To validate the COM framework, we consider a supply chain with one manufacturer and multiple downstream retailers. Retailers privately acquire demand forecast information that they do not have incentive to share horizontally with other …
Self-Organizing Neural Architectures And Cooperative Learning In A Multiagent Environment, Dan Xiao, Ah-Hwee Tan
Self-Organizing Neural Architectures And Cooperative Learning In A Multiagent Environment, Dan Xiao, Ah-Hwee Tan
Research Collection School Of Computing and Information Systems
Temporal-Difference–Fusion Architecture for Learning, Cognition, and Navigation (TD-FALCON) is a generalization of adaptive resonance theory (a class of self-organizing neural networks) that incorporates TD methods for real-time reinforcement learning. In this paper, we investigate how a team of TD-FALCON networks may cooperate to learn and function in a dynamic multiagent environment based on minefield navigation and a predator/prey pursuit tasks. Experiments on the navigation task demonstrate that TD-FALCON agent teams are able to adapt and function well in a multiagent environment without an explicit mechanism of collaboration. In comparison, traditional Q-learning agents using gradient-descent-based feedforward neural networks, trained with the …
Understanding Highly Competent Information System Users, Brenda Eschenbrenner, Fiona Fui-Hoon Nah
Understanding Highly Competent Information System Users, Brenda Eschenbrenner, Fiona Fui-Hoon Nah
Research Collection School Of Computing and Information Systems
Individuals differ in their abilities to use information systems (IS) effectively, with some achieving exceptional performance in IS use. Using the Repertory Grid Technique, this research identifies attributes of highly competent IS users that distinguish them from less competent users. Using the Grounded Theory approach, we identified categories and sub-categories of these attributes and used them to develop a conceptual framework to explain IS User Competency. The findings indicate that highly competent users differ from less competent users in their Personality Traits and Disposition Factors, General Cognitive Abilities, Social Skills and Tendencies, Experiential Learning Factors, Domain Knowledge of and Skills …
An Empirical Analysis Of Mobile Voice Service And Sms: A Structural Model, Youngsoo Kim, William B. Vogt, Ramayya Krishnan, Rahul Telang
An Empirical Analysis Of Mobile Voice Service And Sms: A Structural Model, Youngsoo Kim, William B. Vogt, Ramayya Krishnan, Rahul Telang
Research Collection School Of Computing and Information Systems
In addition to the wireless telephony boom, a similar exponential increasing trend in wireless data service - short message service (SMS) - is visible as technology advances. We develop a structural model to understand how mobile users behave, especially how they consume voice, and services. Specifically, we measure the own- and the cross-price elasticities of these services. The cross-price elasticity is of significant importance because marketing activities are critically influenced by whether the goods are substitutes or complements. The research context poses significant econometric challenges due to three-part tariff, sequential discrete plan choice and continuous quantity choices. Using detailed individual …
Preventing Location-Based Identity Inference In Anonymous Spatial Queries, Panos Kalnis, Gabriel Ghinita, Kyriakos Mouratidis, Dimitris Papadias
Preventing Location-Based Identity Inference In Anonymous Spatial Queries, Panos Kalnis, Gabriel Ghinita, Kyriakos Mouratidis, Dimitris Papadias
Research Collection School Of Computing and Information Systems
The increasing trend of embedding positioning capabilities (for example, GPS) in mobile devices facilitates the widespread use of location-based services. For such applications to succeed, privacy and confidentiality are essential. Existing privacy-enhancing techniques rely on encryption to safeguard communication channels, and on pseudonyms to protect user identities. Nevertheless, the query contents may disclose the physical location of the user. In this paper, we present a framework for preventing location-based identity inference of users who issue spatial queries to location-based services. We propose transformations based on the well-established K-anonymity concept to compute exact answers for range and nearest neighbor search, without …