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Wang-Chien Lee

Bio: Wang-Chien Lee is an academic researcher from Pennsylvania State University. The author has contributed to research in topics: Wireless sensor network & Nearest neighbor search. The author has an hindex of 60, co-authored 366 publications receiving 14123 citations. Previous affiliations of Wang-Chien Lee include Ohio State University & Verizon Communications.


Papers
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Proceedings ArticleDOI
21 Aug 2011
TL;DR: A semantic annotation technique for location-based social networks to automatically annotate all places with category tags which are a crucial prerequisite for location search, recommendation services, or data cleaning is developed.
Abstract: In this paper, we develop a semantic annotation technique for location-based social networks to automatically annotate all places with category tags which are a crucial prerequisite for location search, recommendation services, or data cleaning. Our annotation algorithm learns a binary support vector machine (SVM) classifier for each tag in the tag space to support multi-label classification. Based on the check-in behavior of users, we extract features of places from i) explicit patterns (EP) of individual places and ii) implicit relatedness (IR) among similar places. The features extracted from EP are summarized from all check-ins at a specific place. The features from IR are derived by building a novel network of related places (NRP) where similar places are linked by virtual edges. Upon NRP, we determine the probability of a category tag for each place by exploring the relatedness of places. Finally, we conduct a comprehensive experimental study based on a real dataset collected from a location-based social network, Whrrl. The results demonstrate the suitability of our approach and show the strength of taking both EP and IR into account in feature extraction.

243 citations

Proceedings Article
23 Sep 2007
TL;DR: A suite of novel and efficient skyline algorithms are developed, which scale very well to data dimensionality and cardinality, and soundly outperforms the state-of-the-art skyline algorithms in their specialized domains.
Abstract: Given a set of multidimensional data points, skyline query retrieves a set of data points that are not dominated by any other points. This query is useful for multi-preference analysis and decision making. By analyzing the skyline query, we observe a close connection between Z-order curve and skyline processing strategies and propose to use a new index structure called ZBtree, to index and store data points based on Z-order curve. We develop a suite of novel and efficient skyline algorithms, which scale very well to data dimensionality and cardinality, including (1) ZSearch, which processes skyline queries and supports progressive result delivery; (2) ZUpdate, which facilitates incremental skyline result maintenance; and (3) k-ZSearch, which answers k-dominant skyline query (a skyline variant that retrieves a representative subset of skyline results). Extensive experiments have been conducted to evaluate our proposed algorithms and compare them against the best available algorithms designed for skyline search, skyline result update, and k-dominant skyline search, respectively. The result shows that our algorithms, developed coherently based on the same ideas and concepts, soundly outperforms the state-of-the-art skyline algorithms in their specialized domains.

203 citations

Proceedings ArticleDOI
01 May 2007
TL;DR: This work argues that, once the trajectory of a user is identified, locations of the user is exposed and it's critical to protect the moving trajectories of mobile users in order to preserve user location privacy and proposes two schemes that generate consistent movement patterns in a long run.
Abstract: Dummy-based anonymization techniques for protecting location privacy of mobile users have been proposed in the literature. By generating dummies that move in humanlike trajectories, shows that location privacy of mobile users can be preserved. However, by monitoring long-term movement patterns of users, the trajectories of mobile users can still be exposed. We argue that, once the trajectory of a user is identified, locations of the user is exposed. Thus, it's critical to protect the moving trajectories of mobile users in order to preserve user location privacy. We propose two schemes that generate consistent movement patterns in a long run. Guided by three parameters in user specified privacy profile, namely, short- term disclosure, long-term disclosure and distance deviation, the proposed schemes derive movement trajectories for dummies. A preliminary performance study shows that our approach is more effective than existing work in protecting moving trajectories of mobile users and their location privacy.

199 citations

Patent
09 Oct 2001
TL;DR: A system and a method for synchronizing and updating a relational database with supplemental data in which the relational database has a set of tables defined by a relational schema is proposed in this article.
Abstract: A system and a method for synchronizing and updating a relational database with supplemental data in which the relational database has a set of tables defined by a relational schema. The supplemental data preferably comprises data in a tagged format having a document-type definition representative of the relational schema and is represented in a document object. The system and method preferably ensure record-by-record updating and synchronization of the relational database with the at least one proposed data update by receiving at least one proposed data update from a source external to the relational database; and propagating the received at least one proposed data update into the relational database. In this matter, the compliance with both the relational database relational schema and the tagged data document type definition is ensured without requiring reloading existing data in the relational database.

195 citations

Journal ArticleDOI
TL;DR: Location-dependent information services have great promise for mobile and pervasive computing environments as discussed by the authors and can provide local and nonlocal news, weather, and traffic reports as well as directory services.
Abstract: Location-dependent information services have great promise for mobile and pervasive computing environments. They can provide local and nonlocal news, weather, and traffic reports as well as directory services. Before they can be implemented on a large scale, however, several research issues must be addressed.

195 citations


Cited by
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01 Jan 2002

9,314 citations

Journal ArticleDOI

6,278 citations

Proceedings ArticleDOI
21 Aug 2011
TL;DR: A model of human mobility that combines periodic short range movements with travel due to the social network structure is developed and it is shown that this model reliably predicts the locations and dynamics of future human movement and gives an order of magnitude better performance.
Abstract: Even though human movement and mobility patterns have a high degree of freedom and variation, they also exhibit structural patterns due to geographic and social constraints. Using cell phone location data, as well as data from two online location-based social networks, we aim to understand what basic laws govern human motion and dynamics. We find that humans experience a combination of periodic movement that is geographically limited and seemingly random jumps correlated with their social networks. Short-ranged travel is periodic both spatially and temporally and not effected by the social network structure, while long-distance travel is more influenced by social network ties. We show that social relationships can explain about 10% to 30% of all human movement, while periodic behavior explains 50% to 70%. Based on our findings, we develop a model of human mobility that combines periodic short range movements with travel due to the social network structure. We show that our model reliably predicts the locations and dynamics of future human movement and gives an order of magnitude better performance than present models of human mobility.

2,922 citations

01 Nov 2008

2,686 citations

Journal ArticleDOI
TL;DR: This review presents the emergent field of temporal networks, and discusses methods for analyzing topological and temporal structure and models for elucidating their relation to the behavior of dynamical systems.
Abstract: A great variety of systems in nature, society and technology -- from the web of sexual contacts to the Internet, from the nervous system to power grids -- can be modeled as graphs of vertices coupled by edges The network structure, describing how the graph is wired, helps us understand, predict and optimize the behavior of dynamical systems In many cases, however, the edges are not continuously active As an example, in networks of communication via email, text messages, or phone calls, edges represent sequences of instantaneous or practically instantaneous contacts In some cases, edges are active for non-negligible periods of time: eg, the proximity patterns of inpatients at hospitals can be represented by a graph where an edge between two individuals is on throughout the time they are at the same ward Like network topology, the temporal structure of edge activations can affect dynamics of systems interacting through the network, from disease contagion on the network of patients to information diffusion over an e-mail network In this review, we present the emergent field of temporal networks, and discuss methods for analyzing topological and temporal structure and models for elucidating their relation to the behavior of dynamical systems In the light of traditional network theory, one can see this framework as moving the information of when things happen from the dynamical system on the network, to the network itself Since fundamental properties, such as the transitivity of edges, do not necessarily hold in temporal networks, many of these methods need to be quite different from those for static networks

2,452 citations