64,982 research outputs found
Mining and Clustering of Location Based Services on Basis of Moving Transactions
ABSTRACT: In today's world everything is fast paced and internet as become necessity of life we need it at every step. With the invention of smart phone GPS enabled cell user can ask for any service via Information service and Application provider from anywhere any time. This business model is known as moving commerce .It provides Location based services through moving phone. One of the active topics in mining is the mining and prediction of moving movements and associated transactions. Most of existing studies focus on discovering moving patterns from the whole logs. The issue with this method is that it does not provide accurate information as it depends on spatial clustering where as Location based services require non spatial clustering. The other issue with it is that most methods requires user to set the parameters which is highly impossible in an active environment. Moreover in moving environment the user profiles are seldom known but what we know is the moving transaction patterns. In the paper we will use an algorithm, namely, Temporal Moving Sequential Pattern Mine based on clustering, to discover the Cluster-based Temporal Moving Sequential Patterns .User clusters are constructed by a algorithm named ClusterObject-based Smart Cluster Affinity Search Technique similarities between users are evaluated by the proposed measure, Location-Based Service Alignment (LBS-Alignment).In the algorithm is also proposed to use time as also one of the dimensions where similar moving characteristics exist
Moving Object Trajectories Meta-Model And Spatio-Temporal Queries
In this paper, a general moving object trajectories framework is put forward
to allow independent applications processing trajectories data benefit from a
high level of interoperability, information sharing as well as an efficient
answer for a wide range of complex trajectory queries. Our proposed meta-model
is based on ontology and event approach, incorporates existing presentations of
trajectory and integrates new patterns like space-time path to describe
activities in geographical space-time. We introduce recursive Region of
Interest concepts and deal mobile objects trajectories with diverse
spatio-temporal sampling protocols and different sensors available that
traditional data model alone are incapable for this purpose.Comment: International Journal of Database Management Systems (IJDMS) Vol.4,
No.2, April 201
PATH: Person Authentication using Trace Histories
In this paper, a solution to the problem of Active Authentication using trace
histories is addressed. Specifically, the task is to perform user verification
on mobile devices using historical location traces of the user as a function of
time. Considering the movement of a human as a Markovian motion, a modified
Hidden Markov Model (HMM)-based solution is proposed. The proposed method,
namely the Marginally Smoothed HMM (MSHMM), utilizes the marginal probabilities
of location and timing information of the observations to smooth-out the
emission probabilities while training. Hence, it can efficiently handle
unforeseen observations during the test phase. The verification performance of
this method is compared to a sequence matching (SM) method , a Markov
Chain-based method (MC) and an HMM with basic Laplace Smoothing (HMM-lap).
Experimental results using the location information of the UMD Active
Authentication Dataset-02 (UMDAA02) and the GeoLife dataset are presented. The
proposed MSHMM method outperforms the compared methods in terms of equal error
rate (EER). Additionally, the effects of different parameters on the proposed
method are discussed.Comment: 8 pages, 9 figures. Best Paper award at IEEE UEMCON 201
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