STATE-OF-THE-ART, CHALLENGES: PRIVACY PROVISIONING IN TTP LOCATION BASED SERVICES SYSTEMS

2019 ◽  
Vol 10 (2) ◽  
pp. 68-75 ◽  
Author(s):  
Muhammad Usman Ashraf ◽  
Keyword(s):  
State Of The Art ◽  
Location Based Services

Location-Based Services: The State of the Art

2003 ◽  
Vol 2 (3) ◽  
pp. 59-70 ◽  
Author(s):  
Stuart (Stuart J.) Barnes
Keyword(s):  
State Of The Art ◽  
The State ◽  
Location Based Services

scholarly journals Discovering Subsequence Patterns for Next POI Recommendation

2020 ◽  
Author(s):  
Kangzhi Zhao ◽  
Yong Zhang ◽  
Hongzhi Yin ◽  
Jin Wang ◽  
Kai Zheng ◽  
...  
Keyword(s):  
Power Law ◽  
Domain Knowledge ◽  
State Of The Art ◽  
Location Based Services ◽  
Sequential Patterns ◽  
Economic Activities ◽  
Point Of Interest ◽  
Poi Recommendation ◽  
Latent Structures ◽  
Real World Datasets

Next Point-of-Interest (POI) recommendation plays an important role in location-based services. State-of-the-art methods learn the POI-level sequential patterns in the user's check-in sequence but ignore the subsequence patterns that often represent the socio-economic activities or coherence of preference of the users. However, it is challenging to integrate the semantic subsequences due to the difficulty to predefine the granularity of the complex but meaningful subsequences. In this paper, we propose Adaptive Sequence Partitioner with Power-law Attention (ASPPA) to automatically identify each semantic subsequence of POIs and discover their sequential patterns. Our model adopts a state-based stacked recurrent neural network to hierarchically learn the latent structures of the user's check-in sequence. We also design a power-law attention mechanism to integrate the domain knowledge in spatial and temporal contexts. Extensive experiments on two real-world datasets demonstrate the effectiveness of our model.

scholarly journals MFNP: A Meta-optimized Model for Few-shot Next POI Recommendation

2021 ◽  
Author(s):  
Huimin Sun ◽  
Jiajie Xu ◽  
Kai Zheng ◽  
Pengpeng Zhao ◽  
Pingfu Chao ◽  
...  
Keyword(s):  
State Of The Art ◽  
Cold Start ◽  
User Preferences ◽  
Location Based Services ◽  
Point Of Interest ◽  
Poi Recommendation ◽  
Meta Learning ◽  
Optimized Model ◽  
Real World Datasets ◽  
Cold Start Problem

Next Point-of-Interest (POI) recommendation is of great value for location-based services. Existing solutions mainly rely on extensive observed data and are brittle to users with few interactions. Unfortunately, the problem of few-shot next POI recommendation has not been well studied yet. In this paper, we propose a novel meta-optimized model MFNP, which can rapidly adapt to users with few check-in records. Towards the cold-start problem, it seamlessly integrates carefully designed user-specific and region-specific tasks in meta-learning, such that region-aware user preferences can be captured via a rational fusion of region-independent personal preferences and region-dependent crowd preferences. In modelling region-dependent crowd preferences, a cluster-based adaptive network is adopted to capture shared preferences from similar users for knowledge transfer. Experimental results on two real-world datasets show that our model outperforms the state-of-the-art methods on next POI recommendation for cold-start users.

Engineering Location-Based Services in the Web

2005 ◽  
pp. 114-131
Author(s):  
Silvia Gordillo ◽  
Javier Bazzocco ◽  
Gustavo Rossi ◽  
Robert Laurini
Keyword(s):  
Web Applications ◽  
State Of The Art ◽  
Object Oriented ◽  
Location Based Services ◽  
Design Approach ◽  
Modular Approach ◽  
Design Problems ◽  
Research Issues ◽  
Object Oriented Design ◽  
The Web

In this chapter, we will present a modular approach for building evolvable location-based services in the context of Web applications. We first motivate our research by discussing the state of the art of location-based services; next we analyze which design problems we face while building this kind of application, stressing those problems related with the application’s evolution. We present an object-oriented design approach for engineering location-based applications that effectively supports the evolution of these applications rather than their revolution and give a few examples of its use. We finally discuss some further research issues not explicitly addressed in this chapter.

Device-to-Device Communications

2016 ◽  
pp. 234-255
Author(s):  
Ioannis Giannoulakis ◽  
Emmanouil Kafetzakis ◽  
Anastasios Kourtis
Keyword(s):  
Resource Management ◽  
Social Networking ◽  
Cooperative Communications ◽  
State Of The Art ◽  
Location Based Services ◽  
Future Research ◽  
D2d Communications ◽  
Research Directions ◽  
Device To Device ◽  
Future Research Directions

This chapter provides an account of the most significant areas of scenarios and applications relevant to Device-To-Device (D2D) communications. At first, a state of the art review is provided, with focus on the special technological challenges. In addition, integration initiatives with modern cellular technologies and standards are given. Important architecture concepts like e.g., resource management and mobility issues have been highlighted, in order to present the main areas of impact of D2D communications. Since D2D communications capitalise on the contemporary networking paradigm of cooperative communications novel methods for overcoming several limitations have been discussed and emerging paradigms such as proximity and location-based services, coupled with social networking and commercial services have been considered. Finally, possible future research directions relevant to D2D networking are discussed.

Location-Based Services and Navigation in Smart Phones

2012 ◽  
pp. 196-229
Author(s):  
Ling Pei ◽  
Zhengjun Liu
Keyword(s):  
Communication Networks ◽  
Basic Concept ◽  
State Of The Art ◽  
Smart Phone ◽  
The State ◽  
Location Based Services ◽  
Smart Phones ◽  
Technical Solutions ◽  
New Generation

The ubiquitous positioning ability and abundant computation capability of a smart phone allow the provision of a variety of location-based services (LBSs). This chapter focuses on the fundamental elements and principles of LBS in a smart phone. First, the basic concept of LBS is introduced. Second, the state-of-the-art smart phones and communication networks are described. Afterwards, the smart phone positioning technologies are presented as three groups: satellite-based technologies, network-based solutions, and sensor-based approaches. Then, the location relevant services, contents, data, and context in a smart phone are explained. Furthermore, in the perspective of the new generation of LBS, the emerging features and technical solutions are discussed. Finally, three examples show how the above elements are integrated into the LBS applications in a smart phone.

scholarly journals Accurate and Robust Floor Positioning in Complex Indoor Environments

Sensors ◽  
2020 ◽  
Vol 20 (9) ◽  
pp. 2698
Author(s):  
Jingyu Huang ◽  
Haiyong Luo ◽  
Wenhua Shao ◽  
Fang Zhao ◽  
Shuo Yan
Keyword(s):  
Motion Detection ◽  
State Of The Art ◽  
Barometric Pressure ◽  
Indoor Positioning ◽  
Location Based Services ◽  
Estimation Methods ◽  
Indoor Environments ◽  
Positioning Method ◽  
Application Requirements

With the widespread development of location-based services, the demand for accurate indoor positioning is getting more and more urgent. Floor positioning, as a prerequisite for indoor positioning in multi-story buildings, is particularly important. Though lots of work has been done on floor positioning, the existing studies on floor positioning in complex multi-story buildings with large hollow areas through multiple floors still cannot meet the application requirements because of low accuracy and robustness. To obtain accurate and robust floor estimation in complex multi-story buildings, we propose a novel floor positioning method, which combines the Wi-Fi based floor positioning (BWFP), the barometric pressure-based floor positioning (BPFP) with HMM and the XGBoost based user motion detection. Extensive experiments show that using our proposed method can achieve 99.2% accuracy, which outperforms other state-of-the-art floor estimation methods.

scholarly journals Cloud Platforms for Context-Adaptive Positioning and Localisation in GNSS-Denied Scenarios—A Systematic Review

Sensors ◽  
2021 ◽  
Vol 22 (1) ◽  
pp. 110
Author(s):  
Darwin Quezada-Gaibor ◽  
Joaquín Torres-Sospedra ◽  
Jari Nurmi ◽  
Yevgeni Koucheryavy ◽  
Joaquín Huerta
Keyword(s):  
Systematic Review ◽  
Cloud Computing ◽  
Fault Tolerance ◽  
State Of The Art ◽  
Comprehensive Analysis ◽  
Cloud Services ◽  
Location Based Services ◽  
Efficient Computation ◽  
Key Features ◽  
Essential Resource

Cloud Computing and Cloud Platforms have become an essential resource for businesses, due to their advanced capabilities, performance, and functionalities. Data redundancy, scalability, and security, are among the key features offered by cloud platforms. Location-Based Services (LBS) often exploit cloud platforms to host positioning and localisation systems. This paper introduces a systematic review of current positioning platforms for GNSS-denied scenarios. We have undertaken a comprehensive analysis of each component of the positioning and localisation systems, including techniques, protocols, standards, and cloud services used in the state-of-the-art deployments. Furthermore, this paper identifies the limitations of existing solutions, outlining shortcomings in areas that are rarely subjected to scrutiny in existing reviews of indoor positioning, such as computing paradigms, privacy, and fault tolerance. We then examine contributions in the areas of efficient computation, interoperability, positioning, and localisation. Finally, we provide a brief discussion concerning the challenges for cloud platforms based on GNSS-denied scenarios.

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