Data Mining - Concepts and Techniques.

Statistics for Spatial Data.

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.

/pdf/friendship-and-mobility-user-movement-in-location-based-2u0rrxuc9l.pdf

Friendship and mobility: user movement in location-based social networks

The theory of affordances

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

Temporal Networks

Skyline queries have received a lot of attention from database and information retrieval research communities. A skyline query returns a set of data objects that is not dominated by any other data objects in a given dataset. However, most of existing studies focus on skyline query processing in centralized systems. Only recently, skyline queries are considered in a distributed computing environment. Acknowledging the trend toward peer-to-peer (P2P) systems in distributed computing, we examine the problem of skyline query processing in P2P systems and propose innovative solutions. We exploit the data semantic embedded in semantically structured P2P overlay networks to efficiently prune search space, without compromising the quality of query result. In addition, we propose approximate algorithms to support skyline queries where exact answers are too costly to obtain. These approximate algorithms produce high quality answers using heuristics based on local semantics of peer nodes. Extensive experiments validate that our algorithms provides high efficiency and scalability to skyline query processing in P2P systems.

http://www.cse.psu.edu/~wul2/Publications/wlee%20Infoscale06b.pdf

Efficient progressive processing of skyline queries in peer-to-peer systems

We discuss several channel allocation methods for data dissemination in mobile computing systems. We suggest that the broadcast and on-demand channels have different access performance under different system parameters and that a mobile cell should use a combination of both to obtain optimal access time for a given workload and system parameters. We study the data access efficiency of three channel configurations: all channels are used as on-demand channels (exclusive on-demand); all channels are used for broadcast (exclusive broadcast); and some channels are on-demand channels and some are broadcast channels (hybrid). Simulations on obtaining the optimal channel allocation for lightly-loaded, medium-loaded, and heavy-loaded conditions is conducted and the result shows that an optimal channel allocation significantly improves the system performance.

/pdf/channel-allocation-methods-for-data-dissemination-in-mobile-32zsewqx8y.pdf

Channel allocation methods for data dissemination in mobile computing environments

Due to the growing interest in XML security, various access control schemes have been proposed recently. However, little effort has been put forth to facilitate a uniform analysis and comparison of these schemes under the same framework. This paper presents a first attempt toward a flexible framework that can capture the design principles and operations of existing XML access control mechanisms. Under this framework, we observe that most existing XML access control mechanisms share the same design principle with slightly different orderings of underlying building blocks (i.e., data, query, and access control rule). Furthermore, according to the framework, we identify four plausible approaches to implement XML access controls, namely built-in, view-based, pre-processing and post-processing. Finally, we compare the actual performance of different approaches.

/pdf/a-flexible-framework-for-architecting-xml-access-control-2il1zstl8x.pdf

A Flexible Framework for Architecting XML Access Control Enforcement Mechanisms

In this paper, we introduce the notion of sufficient set and necessary set for distributed processing of probabilistic top-k queries in cluster-based wireless sensor networks. These two concepts have very nice properties that can facilitate localized data pruning in clusters. Accordingly, we develop a suite of algorithms, namely, sufficient set-based (SSB), necessary set-based (NSB), and boundary-based (BB), for intercluster query processing with bounded rounds of communications. Moreover, in responding to dynamic changes of data distribution in the network, we develop an adaptive algorithm that dynamically switches among the three proposed algorithms to minimize the transmission cost. We show the applicability of sufficient set and necessary set to wireless sensor networks with both two-tier hierarchical and tree-structured network topologies. Experimental results show that the proposed algorithms reduce data transmissions significantly and incur only small constant rounds of data communications. The experimental results also demonstrate the superiority of the adaptive algorithm, which achieves a near-optimal performance under various conditions.

Distributed Processing of Probabilistic Top-k Queries in Wireless Sensor Networks

Road network is a basic component of intelligent transportation systems (ITS) in smart city. Informative representation of road networks is important as it is essential to a wide variety of ITS applications. In this paper, we propose a neural network representation learning model, namely Intersection of Road Network to Vector (IRN2Vec), to learn embeddings of road intersections that encode rich information in a road network by exploring geo-locality and intrinsic properties of intersections and moving behaviors of road users. In addition to model design, several issues unique to IRN2Vec, including data preparation for model training and various relationships among intersections, are examined. We evaluate the learned embeddings via extensive experiments on three real-world datasets using three downstream test cases, including prediction of traffic signals and crossings on intersections and travel time estimation. Experimental results show that the proposed IRN2Vec outperforms three existing methods, DeepWalk, LINE and Node2vec, in terms of F1-score in predicting traffic signals (22.21% to 23.84%) and crossings (8.65% to 11.65%), and mean absolute error (MAE) in travel time estimation (9.87% to 19.28%).

/pdf/learning-embeddings-of-intersections-on-road-networks-2eq5lhiuk1.pdf

Wang-Chien Lee

Papers

Efficient progressive processing of skyline queries in peer-to-peer systems

Channel allocation methods for data dissemination in mobile computing environments

A Flexible Framework for Architecting XML Access Control Enforcement Mechanisms

Distributed Processing of Probabilistic Top-k Queries in Wireless Sensor Networks

Learning Embeddings of Intersections on Road Networks