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Demographic Attributes Prediction on the Real-World Mobile Data
"... The deluge of the data generated by mobile phone devices imposes new challenges on the data mining community. User activities recorded by mobile phones could be useful for uncovering behavioral patterns. An interesting question is whether patterns in mobile phone usage can reveal demographic charact ..."
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The deluge of the data generated by mobile phone devices imposes new challenges on the data mining community. User activities recorded by mobile phones could be useful for uncovering behavioral patterns. An interesting question is whether patterns in mobile phone usage can reveal demographic characteristics of the user? Demographic information about gender, age, marital status, job type, etc. is a key for applications with customer centric strategies. In this paper, we describe our approach to feature extraction from raw data and building predictive models for the task of demographic attributes predictions. We experimented with graph based representation of users inferred from similarity of their feature vectors, feature selections and classifications algorithms. Our work contributes to the Nokia Mobile Data Challenge (MDC) in the endeavor of exploring the real-world mobile data.
Chapter 8 Location-Based Social Networks: Users
"... Abstract In this chapter, we introduce and define the meaning of location-based social network (LBSN) and discuss the research philosophy behind LBSNs from the perspective of users and locations. Under the circumstances of trajectory-centric LBSN, we then explore two fundamental research points conc ..."
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Abstract In this chapter, we introduce and define the meaning of location-based social network (LBSN) and discuss the research philosophy behind LBSNs from the perspective of users and locations. Under the circumstances of trajectory-centric LBSN, we then explore two fundamental research points concerned with understanding users in terms of their locations. One is modeling the location history of an individual using the individual’s trajectory data. The other is estimating the similarity between two different people according to their location histories. The inferred similarity represents the strength of connection between two users in a locationbased social network, and can enable friend recommendations and community discovery. The general approaches for evaluating these applications are also presented.
Experimentation, Performance
"... A socio-spatial graph is a combination of a social network with a spatial network. In such graph, the social network contains information on users and about the social relationships among these users. The spatial network contains information on geographic entities and about the spatial relationships ..."
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A socio-spatial graph is a combination of a social network with a spatial network. In such graph, the social network contains information on users and about the social relationships among these users. The spatial network contains information on geographic entities and about the spatial relationships among these entities. Users are associated with geographic locations using life-pattern edges. The life pattern edges synopsize the location history of people, and accordingly, connect individuals to places they frequently visit. Such graphs are used to provide information on people, while taking into account the spatial whereabout of individuals, and to provide information on geographical entities, in correspondence with their social aspects, i.e., according to the people visited in these entities. Thus, socio-spatial graphs are important analytic tools, however, when they combine a large social network with a large spatial network, the result is a large graph. In this paper we show how to efficiently build such large graphs and how to query them effectively.
Crowd Location Forecasting at Points of Interest
"... Abstract: Predicting the location of a mobile user in the near future can be used for a large number of user-centered ubiquitous applications. This can be extended to crowd-centered applications if a large number of users is included. In this paper we present a spatio-temporal prediction approach to ..."
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Abstract: Predicting the location of a mobile user in the near future can be used for a large number of user-centered ubiquitous applications. This can be extended to crowd-centered applications if a large number of users is included. In this paper we present a spatio-temporal prediction approach to forecast user location in a medium-term period. Our approach is based on the hypothesis that users exhibit a different mobility pattern for each day of the week. Once factored out this weekly pattern, user mobility among points of interest is postulated to be markovian. We trained a hidden Markov model to forecast user mobility and evaluated our approach using a public dataset. The experimental results show that our approach is effective considering a time period of up to seven hours. We obtained an accuracy of up to 81.75 % for a period of 30 minutes, and 66.25 % considering 7 hours.
Mobile Data Delivery through Opportunistic Communications among Cellular Users: A Case
"... The appearance of smartphones and increasing popularity of various mobile applications and services have caused the ex-plosion of mobile data traffic. To avoid overloading the cellu-lar networks, different offloading solutions (such as WiFi net-works or femtocells) have been proposed and adopted. Re ..."
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The appearance of smartphones and increasing popularity of various mobile applications and services have caused the ex-plosion of mobile data traffic. To avoid overloading the cellu-lar networks, different offloading solutions (such as WiFi net-works or femtocells) have been proposed and adopted. Re-cently, offloading cellular traffic through opportunistic com-munications among mobile phones becomes a new and promis-ing option, due to free cost. In this paper, by using real trace data from the Orange “Data for Development ” (D4D) challenge, we investigate the feasibility of delivering data packets among mobile cellular users through opportunistic communications in a large scale network. Our experimental results show that by using social or location properties of mobile users opportunistic routing can indeed complement the traditional cellular network to deliver delay-tolerant data packets among certain portion of cellular users. Such solu-tion is especially cost efficient and beneficial for developing countries, as Ivory Coast. 1.
What’s Your Next Move: User Activity Prediction in Location-based Social Networks
"... Location-based social networks have been gaining increasing popularity in recent years. To increase users ’ engagement with location-based services, it is important to provide attractive features, one of which is geo-targeted ads and coupons. To make ads and coupon delivery more effective, it is ess ..."
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Location-based social networks have been gaining increasing popularity in recent years. To increase users ’ engagement with location-based services, it is important to provide attractive features, one of which is geo-targeted ads and coupons. To make ads and coupon delivery more effective, it is essential to predict the location that is most likely to be visited by a user at the next step. However, an inherent challenge in location prediction is a huge prediction space, with millions of distinct check-in locations as prediction target. In this paper we exploit the check-in category information to model the underlying user movement pattern. We propose a framework which uses a mixed hidden Markov model to predict the category of user activity at the next step and then predict the most likely location given the estimated category distribution. The advantages of modeling the category level include a significantly reduced prediction space and a precise expression of the semantic meaning of user activities. Extensive experimental results show that, with the predicted category distribution, the number of location candidates for prediction is 5.45 times smaller, while the prediction accuracy is 13.21 % higher. 1
1 Mining Fastest Path from Trajectories with Multiple Destinations in Road Networks
"... Abstract: Nowadays, research on Intelligent Transportation System (ITS) has received many attentions due to its broad applications such as path planning which has become a common activity in our daily life. Besides, with the advances of Web 2.0 technologies, users are willing to share their trajecto ..."
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Abstract: Nowadays, research on Intelligent Transportation System (ITS) has received many attentions due to its broad applications such as path planning which has become a common activity in our daily life. Besides, with the advances of Web 2.0 technologies, users are willing to share their trajectories, thus providing good resources for ITS applications. To our best knowledge, there is no study on the fastest path planning with multiple destinations in the literature. In this paper, we develop a novel framework, called Trajectory-based Path Finding (TPF), which is built upon a novel algorithm named Mining-based Algorithm for Travel time Evaluation (MATE) for evaluating the travel time of a navigation path and a novel index structure named Efficient Navigation Path Search Tree (ENS-Tree) for efficiently retrieving the fastest path. With MATE and ENS-tree, an efficient fastest path finding algorithm for single destination is derived. To find the path for multiple destinations, we propose a novel strategy, named Cluster-Based Approximation Strategy (CBAS), to determine the fastest visiting order from specified multiple destinations. Through a comprehensive set of experiments, we evaluate the proposed techniques employed in the design of TPF and show that MATE, ENS-tree and CBAS produce excellent performance under various system conditions.
Corresponding Author: S. Jacinth Evangeline 30 Efficiently Mining the Frequent Patterns in Mobile Commerce Environment
"... Copyright © 2014 ISSR Journals. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. ABSTRACT: Nowadays, a rapid development in the commun ..."
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Copyright © 2014 ISSR Journals. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. ABSTRACT: Nowadays, a rapid development in the communication technology and increasing the usability of powerful portable devices, mobile users can use their mobile devices to access the information. One of the active areas is the mining and prediction of users ’ mobile commerce behaviors such as their movements and purchase transactions. The important issue is to mine the rare frequent items from database to satisfy the user needs. In this paper, we propose a technique that can efficiently satisfy the user needs. It predicts the frequent item based on the user selection. Systolic tree implementation is used to predict the frequently moved item in the database. The main aim is to recommend the stores and items previously to unknown user. We evaluate our system in real world and deliver good performance in terms efficiency and scalability.
Recommended Citation
, 2014
"... This dissertation is an in-depth case study of NATO advisors and their perceived influence in Afghanistan (2009-2012). It explores the two-part question, how do foreign security actors (ministerial advisors and security force trainers, advisors, and commanders) attempt to influence their host-nation ..."
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This dissertation is an in-depth case study of NATO advisors and their perceived influence in Afghanistan (2009-2012). It explores the two-part question, how do foreign security actors (ministerial advisors and security force trainers, advisors, and commanders) attempt to influence their host-nation partners and what are their perceptions of these approaches on changes in local capacity, values, and security governance norms? I argue that security sector reform (SSR) programs in fragile states lack an explicit theory of change that specifies how reform occurs. From this view, I theorize internationally led SSR as “guided institutional transfer, ” grounded in rationalist and social constructivist explanations of convergence, diffusion, and socialization processes. Responding to calls for greater depth and emphasis on interactions and institutional change in SSR research, I examine NATO’s efforts in Afghanistan as an extreme case of SSR in which external-internal interactions were the highest. A stratified, purposive sample of 68 military and civilian elites (24 ministerial advisors, 27 embedded field advisors and commanders, and 17 experts and external observers) participated in a confidential, semi-structured interview.
