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.

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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

As data and knowledge volumes keep increasing while global means for information dissemination continue to diversify, new methods, modeling paradigms, and structures are needed to efficiently support the mounting scalability requirements for the large variety of current and future data, information, and knowledge.

Grid computing, P2P technology, data and knowledge bases, distributed information retrieval technology, and networking technology should all converge to address the scalability concern. The Second International Conference on Scalable Information Systems will focus on a wide array of scalability issues and investigate new approaches for tackling problems arising from the ever-growing size and complexity of information of all kinds.

Proceedings of the 2nd international conference on Scalable information systems

Editorial: Special Section: Scalable information systems

Entity resolution has been widely used in data mining applications to find similar records. However, the increasing scale and complexity of data has restricted the performance of entity resolution. In this paper, we propose a novel entity resolution framework that clusters large-scale data with distributed entity resolution method. We model the clustering problem as finding similarity sub connected graphs from records. Firstly, our approach finds pairs of records whose similarities are above a given threshold based on appjoin algorithm which extends the ppjoin algorithm and are executed on MapReduce framework. Then, we propose a cache-based algorithm which cluster entities with similar pairs based on the Disjoin Set algorithm and are also designed for MapReduce framework. Experimental results on real dataset show that our algorithms can achieve more efficiency than previous algorithms on the entity resolution and clustering.

Distributed Entity Resolution Based on Similarity Join for Large-Scale Data Clustering

Dik Lun Lee Wang-Chien Lee Department of Computer Science Dept of Computer and Information Science University of Science and Technology The Ohio State University Clear Water Bay, Hong Kong Columbus, Ohio 43210-1277, USA dlee@cs.ust.hk wlee@cis.ohio-state.edu FAX: (852) 2358-1477 FAX: 614-292-2911 Abstract This paper discusses signature caching strategies to reduce power consumption for wireless broadcast and ltering services. Four caching policies are compared in terms of tune-in time and access time. With reasonable access time delay, all of the caching policies help in reducing tune-in time for the two-level signature scheme. Moreover, two cache replacement policies are presented and compared by simulation. The result shows that, when the cache size is small, caching only the integrated signatures is recommended. When the size of cache is greater than that of the integrated signatures, caching both of the integrated and simple signatures is better.

On Signature Caching of Wireless Broadcast and Filtering Services

To provide secure access to data in wireless broadcast services, symmetric key-based encryption is used to ensure that only users who own the valid keys can decrypt the data. In this paper, we propose an efficient key management scheme (namely KTR) to handle key distribution with regarding to complex subscription options and user activities. KTR has the following advantages. First, it supports all subscription activities in wireless broadcast services. Second, in KTR, a user only needs to hold one set of keys for all subscribed programs, instead of separate sets of keys for each program. Third, KTR identifies the minimum set of keys that must be changed to ensure broadcast security and minimize the rekey cost. Our simulations show that KTR can save about 45% of communication overhead in the broadcast channel and about 50% of decryption cost for each user, compared with conventional approaches based on logical key hierarchy.

http://www.cse.psu.edu/~wul2/Publications/wlee%20Mobiquitous05c.pdf

Wang-Chien Lee

Papers

Proceedings of the 2nd international conference on Scalable information systems

Editorial: Special Section: Scalable information systems

Distributed Entity Resolution Based on Similarity Join for Large-Scale Data Clustering

On Signature Caching of Wireless Broadcast and Filtering Services

KTR: an efficient key management scheme for air access control