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Hybrid Markov Location Prediction Algorithm Based on Dynamic Social Ties
2015
IEICE transactions on information and systems
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A hybrid Markov location prediction algorithm based on dynamic social ties is presented. ...
The experiments based on a real location-based social network dataset show the hybrid Markov location prediction algorithm could improve 15% predictive accuracy compared with the location prediction algorithms ...
Hybrid Markov Model Based on Dynamic Social Ties Order-k Markov model is a very popular model to predict the individual's next location. ...
doi:10.1587/transinf.2014edp7296
fatcat:btvazeguyfa2lepolht34ph4yy
Ensemble mobility predictor based on random forest and Markovian property using LBSN data
2020
Journal of Internet Services and Applications
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In this article, we introduce the Ensemble Random Forest-Markov (ERFM) mobility prediction model, a two-layer ensemble learner approach, in which the base learners are also ensemble learning models. ...
Moreover, this data contains spatial, temporal, and social features of user activity, enabling a system to predict user mobility. ...
The author Denis Rosario would like to thank the National Council for Scientific and Technological Development (CNPq) for the financial support through Grant 431474/2016-8. ...
doi:10.1186/s13174-020-00130-7
fatcat:ae7p7qaf65bf7ayzuis2vzeoce
An Approach for a Next-Word Prediction for Ukrainian Language
2021
Wireless Communications and Mobile Computing
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LSTM and Markov chains and their hybrid were chosen for next-word prediction. ...
The hybrid model presents adequate results but it works slowly. Using the model, user can generate not only one word but also a few or a sentence or several sentences, unlike T9. ...
For achieving better results of the nextword prediction model, it was decided to develop a hybrid of LSTM and Markov chains.
. LSTM Model. ...
doi:10.1155/2021/5886119
fatcat:fp4tne2afbe6tpoka2ofqppokq
A Location Prediction Algorithm with Daily Routines in Location-Based Participatory Sensing Systems
2015
International Journal of Distributed Sensor Networks
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Finally, the UCSD WTD dataset are exploited for simulations. Simulation results show that SMLPR acquires higher prediction accuracy than proposals based on the Markov model. ...
This paper proposes a social-relationship-based mobile node location prediction algorithm using daily routines (SMLPR). ...
Meanwhile, hidden Markov models (HMMs) are also considered to predict human mobility. Literature [17] presents a hybrid method on the basis of hidden Markov models. ...
doi:10.1155/2015/481705
fatcat:d4rufwknozbmrghxmx7zzqruhq
A Study of Mobile User Movements Prediction Methods
2018
International Journal of Electrical and Computer Engineering (IJECE)
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<p>For a decade and more, the Number of smart phone users count increasing day by day. ...
With the drastic improvements in Communication technologies, the prediction of future movements of mobile users needs also have important role. Various sectors can gain from this prediction. ...
Hybrid Method The next Hybrid method, the prediction made as a Service for improve applications as mobility aware personalization and predictive resource allocation. ...
doi:10.11591/ijece.v8i5.pp3112-3117
fatcat:pqw2w2wohrdqnleonj52qolmge
A Survey for the Ranking of Trajectory Prediction Algorithms on Ubiquitous Wireless Sensors
2020
Sensors
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Our results show three top algorithms, namely NextPlace, the Markov model, and the hidden Markov model. ...
Although there is a body of research work regarding motion trajectory prediction, there are no guidelines for choosing algorithms best suited for individual needs in uncertain and complex situations and ...
The hidden Markov model proposes a visit-history-based activity prediction algorithm for services of activity-aware mobile in smart cities named Agatha. ...
doi:10.3390/s20226495
pmid:33203034
fatcat:v26ixokhjneejkv225krlukaya
20 Years of Mobility Modeling Prediction: Trends, Shortcomings Perspectives
[article]
2019
arXiv
pre-print
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We also observe troubling trends with respect to application of Markov model variants for modeling mobility, despite the questionable association of Markov processes and human-mobility dynamics. ...
In this paper, we present a comprehensive survey of human-mobility modeling based on 1680 articles published between 1999 and 2019, which can serve as a roadmap for research and practice in this area. ...
(large scale)
Markov model,
Bayesian nets
Markov variants,
Hybrid models
Table 1 : 1 Different variants of Markov models used to model human-mobility, datasets used to corroborate the model ...
arXiv:1906.07451v1
fatcat:yqrwd2zhpvcppdopb3wzakr5b4
An Analysis of Location Prediction Models
2020
International Journal of Computer Applications
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This paper places emphasizes on the relevance of location prediction models in mobile users. ...
Although this article does not give an exhaustive survey of all techniques and applications but it gives a description of several types of algorithms and models used for location prediction. ...
This can aid users in choosing the location predicting model that best suits their need their location. In future this research hopes to expand its scope on more location prediction model. ...
doi:10.5120/ijca2020920063
fatcat:lstc4uzdrbg3pegwzd2ftnrfsy
Editorial: Cognitive Science and Artificial Intelligence for Human Cognition and Communication
2019
Journal on spesial topics in mobile networks and applications
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times and proposed a novel Korder mixed Markov model for predicting the CPU load of the host for a period of time. ...
The first article, BEEDVMI: Energy-Efficient Dynamic Virtual Machines Integration^, authored by Yin Zhang, synthetically considered the influence of a multi-order Markov model and the CPU state at different ...
doi:10.1007/s11036-019-01265-z
fatcat:2wm2v6dg6rcu5cbn75h6ji7axq
A Survey on Next-Cell Prediction in Cellular Networks: Schemes and Applications
2020
IEEE Access
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ACKNOWLEDGMENT The authors would like to thank the anonymous reviewers for their valuable comments and suggestions that helped improve the quality of this paper. ...
The combination of these two methods can predict regular and random movements. A hybrid scheme based on handover history table and realtime GPS for Markov process prediction is described in [84] . ...
In other words, there exists strong regularity in human mobility, and it is theoretically possible to develop accurate prediction models. ...
doi:10.1109/access.2020.3036070
fatcat:p7augewwhfan3ndsgcqqd2mm5q
Mobility Prediction Using a Weighted Markov Model Based on Mobile User Classification
2021
Sensors
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To improve prediction accuracy, this paper proposes a weighted Markov prediction model based on mobile user classification. ...
Finally, according to the characteristics of each user classification, the step threshold and the weighting coefficients of the weighted Markov prediction model are optimized, and mobility prediction is ...
Acknowledgments: The research team would like to thank the anonymous reviewers for their critical comments and suggestions to improve the manuscript. ...
doi:10.3390/s21051740
pmid:33802421
pmcid:PMC7959290
fatcat:3h52ljjhufhwhamgr2avo3b7ei
Predicting future locations with hidden Markov models
2012
Proceedings of the 2012 ACM Conference on Ubiquitous Computing - UbiComp '12
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This paper presents an hybrid method for predicting human mobility on the basis of Hidden Markov Models (HMMs). ...
Tasks such as the prediction of human movement can be addressed through the usage of these data, in turn offering support for more advanced applications, such as adaptive mobile services with proactive ...
Acknowledgements The authors would like to express their gratitude to Fundação para a Ciência e a Tecnologia (FCT), for the financial support offered through the project grant corresponding to Parameters ...
doi:10.1145/2370216.2370421
dblp:conf/huc/MathewRM12
fatcat:4jjspubycfbjniemxh3fiixwgy
MyRoute: A Graph-Dependency Based Model for Real-Time Route Prediction
2017
Journal of Communications
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This paper addresses these issues by proposing a novel dependency-graph based predictor for real-time route prediction, named MyRoute. ...
However, many mobility prediction approaches are not noise tolerant, do not consider collective and individual behavior for making predictions, and provide a low accuracy. ...
[16] have proposed three prediction models: (1) a statistical model based on frequent itemset mining, (2) an n-order Markov model where n<4, and (3) a Pattern Matching Model based on n-order Markov ...
doi:10.12720/jcm.12.12.668-676.
fatcat:quwfcttevbgxzeemclabo7zxs4
Universal Artificial Intelligence for Intelligent Agents: An Approach to Super Intelligent Agents
2013
IOSR Journal of Computer Engineering
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Human beings have the real intelligence. The intelligence triggers new thoughts in mind. Human thoughts so many things but he may take long times to solve a complex problem. ...
Artificial intelligence based system has the ability to mimic the functions of the human brain. An intelligent agent works on behalf of man. ...
A research paper in 2005 uses the hidden markov model for recognition of human motion. A new approach for calculating transition and emission matrices was introduced. ...
doi:10.9790/0661-1264348
fatcat:2z7ds2n5gzhw7luyzmcbbm4gj4
Personalized Check-in Prediction Model Based On User's Dissimilarity and Regression
2019
IEEE Access
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INDEX TERMS Location-based social networks, check-in prediction, hybrid Markov model, kernel density estimation. This work is licensed under a Creative Commons Attribution 3.0 License. ...
To solve the problem that the user check-in prediction model is difficult to provide personalized check-in services, this paper proposes a novel hybrid model, called personalized check-in prediction model ...
[22] proposed a hybrid Markov-based prediction method, which estimated the order of a Markov chain predictor by the length of the user's mobility patterns, and calculated the transition probability ...
doi:10.1109/access.2019.2923435
fatcat:gmajmxcgjrfgjoir2temcggv2u
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