利用情境感知提高LBS适切性的研究

针对目前LBS发展缺乏用户粘性的瓶颈问题,文中提出LBS适切性的概念,并研究了利用情境感知提高这种适切性的关键方法：建立LBS情境知识库和LBS情境推理机。文中预测了情境感知设备的应用,详细讨论了LBS的情境划分,设计了LBS情境感知系统的参考架构、LBS情境知识库的基本结构,以及基于回溯策略的LBS情境推理机实现方法。情境感知使LBS的输入方式,从显示输入为主向隐式输入为主转变,用户在没有任何输入的状态下就能得到适切的服务,这为提高人机交互的简易性、高效性以及LBS系统行为的灵活性和智能性奠定了必要基础。     

Spatial cloaking for anonymous location-based services in mobile peer-to-peer environments

This paper tackles a privacy breach in current location-based services (LBS) where mobile users have to report their exact location information to an LBS provider in order to obtain their desired services. For example, a user who wants to issue a query asking about her nearest gas station has to report her exact location to an LBS provider. However, many recent research efforts have indicated that revealing private location information to potentially untrusted LBS providers may lead to major privacy breaches. To preserve user location privacy, spatial cloaking is the most commonly used privacy-enhancing technique in LBS. The basic idea of the spatial cloaking technique is to blur a user’s exact location into a cloaked area that satisfies the user specified privacy requirements. Unfortunately, existing spatial cloaking algorithms designed for LBS rely on fixed communication infrastructure, e.g., base stations, and centralized/distributed servers. Thus, these algorithms cannot be applied to a mobile peer-to-peer (P2P) environment where mobile users can only communicate with other peers through P2P multi-hop routing without any support of fixed communication infrastructure or servers. In this paper, we propose a spatial cloaking algorithm for mobile P2P environments. As mobile P2P environments have many unique limitations, e.g., user mobility, limited transmission range, multi-hop communication, scarce communication resources, and network partitions, we propose three key features to enhance our algorithm: (1) An information sharing scheme enables mobile users to share their gathered peer location information to reduce communication overhead; (2) A historical location scheme allows mobile users to utilize stale peer location information to overcome the network partition problem; and (3) A cloaked area adjustment scheme guarantees that our spatial cloaking algorithm is free from a “center-of-cloaked-area” privacy attack. Experimental results show that our P2P spatial cloaking algorithm is scalable while guaranteeing the user’s location privacy protection.     

The personalized context‐aware mobile advertisement system using a novel approaching detection method over cellular networks

With the rapid development of smartphones and personal tablet computers, it brings a greatly growing rate of ubiquitous applications for location‐based services (LBS). One famous LBS is the mobile advertisement. A mobile advertisement system brings benefits and opportunities among users, service providers, and advertisers. In this paper, we propose a personalized context‐aware mobile advertisement system (PCA‐MAS) over cellular networks, which contains two new techniques called (i) approaching detection method (ADM) and (ii) context‐aware ad targeting method (CAADTM). ADM can find some point of interests that a user is approaching; CAADTM pushes advertisements that satisfy user's requirement based on the user's context, that is, user's profile, current time, current position, and so on. Our experimental results show that (i) ADM has the good hit rate to determine those point of interests that a user is approaching within the 150‐m radius of the approaching range, and (ii) CAADTM has the good hit rate of finding appropriate advertisements that a user prefers through the favorite content table filtering, the annoying content table filtering, and the advertisement clicking feedback. Copyright © 2013 John Wiley & Sons, Ltd.     

Protecting location privacy in mobile geoservices using fuzzy inference systems

Mobile geoservices, especially location-based services (LBSs), are becoming more popular each day. The most important goal of these services is to use a user’s location to provide location-aware services. Because the user’s spatial information can be abused by organizations or advertisers, and sometimes for criminal purposes, the protection of this information is a necessary part of such services. There has been substantial research on privacy protection in LBSs and mobile geoservices; most studies have attempted to anonymize the user and hide his/her identity or to engage the user in the protection process. The major defects of these previous approaches include an increased complexity of system architecture, a decrease in service capabilities, undesirable processing times, and a failure to satisfy users. Additionally, anonymization is not a suitable solution for context-aware services. Therefore, in this paper, a new approach is proposed to locate users with different levels of spatial precision, based on his/her spatio-temporal context and a user’s group, through fuzzy inference systems. The user’s location and the time of the request determine the spatio-temporal context of the user. A fuzzy rule base is formed separately for each group of users and services. An interview is a simple method to extract the rules. The spatial precision of a user’s location, which is obtained from a fuzzy system, goes to a spatial function called the conceptualization function, to determine the user’s location based on one of the following five levels of qualitative precision: geometrical coordinates, streets, parish, region, and qualitative location, such as the eastern part of the city. Thus, there is no need to anonymize users in mobile geoservices or to turn the service off. The applicability and efficiency of the proposed method are shown for a group of taxi drivers.     

LBS中基于移动终端的连续查询用户轨迹隐匿方法*

为减少现有LBS(基于位置的服务)机制给用户位置信息和个人隐私泄露带来的威胁,提出并实现了一个基于移动智能终端的连续查询用户运动轨迹保护方案.该方法利用移动终端来规划虚拟路径,以减少用户在连续查询中的隐私泄露,且不需要第三方服务器提供位置匿名服务,由用户自主决定何时启动位置隐匿机制.实验证明,提出的方法有效地隐匿了连续查询用户的位置及轨迹信息.     

Remote service discovery and binding architecture for soft real-time QoS in indoor location-based service

Indoor location-based service (LBS) is generally distinguished from web services that have no physical location and user context. In particular, various resources have dynamic and frequent mobility in indoor environments. In addition, an indoor LBS includes numerous service lookups being requested concurrently and frequently from several locations, even through a network infrastructure requiring high scalability in indoor environments. The traditional centralized LBS approach needs to maintain a geographical map of the entire building or complex in its central server, which can cause low scalability and traffic congestion. This paper presents a self-organizing and fully distributed indoor LBS platform with regional cooperation among devices. A service lookup algorithm based on the proposed distributed architecture searches for the shortest physical path to the nearest service resource. A continuous service binding mechanism guarantees a probabilistic real-time QoS regardless of dynamic and frequent mobility in a soft real-time system such as an indoor LBS. Performance evaluation of the proposed algorithm and platform is compared to the traditional centralized architecture in the experimental evaluation of scalability and real test bed environments.     

Personalized Service Discovery in Ubiquitous Computing Environments

In ubiquitous computing environments, users want to discover the most appropriate service to support their tasks. Because the most appropriate service depends on user preferences and context, service discovery protocols should personalize results. A service discovery framework based on the virtual personal space (VPS)-that is, a virtual administrative domain of services managed for the user-aims to provide this personalization. In this framework, personal operating middleware embedded in a personal device manages a set of contextually close services in the user's VPS. An inference module supports this management. Laboratory evaluations show that the VPS framework helps users find high-quality, appropriate services.     

A prediction and auto-execution system of smartphone application services based on user context-awareness

Smartphones have emerged as suitable environments for user context-awareness and intelligent service provision due to the high penetration rate, the high usability, various embedded sensors, and so on. In particular, its most unique characteristic is the usage of various applications. However, the most of existing studies through the three steps process (log collection, context inference, and service provision) did not consider smartphone applications (Apps) as the target service. Smartphone users still have to use Apps with manual controls by own decision. Therefore, in this paper, we propose a system to predict smartphone applications based on inferring user context. We define a mobile context model with a new level of context (Situation) and its inference method to perceive a user’s intention or purpose related to the App usage. Based on the Situation context, the system predicts Apps which can be useful and helpful for a user and automatically executes it on his/her smartphone. With the proposed system, it will be possible to autonomously provide and manage smartphone application services without users’ perception or intervention.     

Interactive middleware architecture for lifelog based context awareness

Due to the development of IT convergence, a wide variety of information is being produced and distributed rapidly in digital form. Lifelog based context awareness is a technology that provides a service automatically based on perceived situational information in ubiquitous environments. To offer customized services to users, the technology of acquiring lifelog based context information in real time is the most important consideration. We propose the interactive middleware architecture for lifelog based context awareness in distributed and ubiquitous environments. Conventional middleware to support ubiquitous environments stores and manages the situational information and service content acquired by centralized storage or a DBMS. Centralized situational information and service content management may impede the autonomy of mobile nodes and the interoperation between different middle software. The proposed method designs a system that can distribute and manage situational information in mobile nodes using mobile devices in distributed and ubiquitous environments and share the service content between interactive middleware through publication. The application system designed in this study was used in a scenario providing situational perception based mobile service and proved to be useful.     

基于LBS的“急速药递”小程序管理系统的设计与实现

为给紧急需要某种药物且意识清醒的用户快速提供药品,研究基于地理位置的药品求助和响应救助具有重要意义。在分析了用户急需某种药品但是无法获得时的需求,设计了基于用户地理位置(LBS)的“急速药递”小程序管理系统,对系统的紧急求助、消息推送、地图显示和基本信息填报等功能模块进行分析与设计,主要运用位置标记的方式展示求助信息、以消息推送的形式通知附近的志愿者或医药机构、地图显示药品求助信息、附近多位商家或志愿者响应求助并快速将药品送达,实现基于LBS的药品需求信息服务。系统采用云开发模式开发,描述了系统实现的关键技术,具有一定的实用价值。     

A study of context inference for Web-based information systems

Recently, context-awareness has been a hot topic in the ubiquitous computing field. Numerous methods for capturing, representing and inferring context have been developed and relevant projects have been performed. Existing research has tried to determine user’s contextual information physically by using stereo type cameras, RFID, smart devices, etc. These are heavily focusing on external context such as location, temperature, light, etc. However, cognitive elements of the context are important and need more study. This paper confines its research domain to the Web-based information system (IS) and, first, proposes two algorithms, the context inference algorithm and the service recommendation algorithm, for inferring cognitive context in the IS domain. Second, this paper demonstrates cognitive context-awareness on the Web-based information systems through implementing prototype deploying the proposed algorithms. The proposed system deploying the context inference and service recommendation algorithm can help the IS user to work with an IS conveniently and enable an existing IS to deliver ubiquitous service. In this fashion, we show the direction of existing IS and, ultimately, shows the typical services of a ubiquitous computing-based IS.     

Landscape-aware location-privacy protection in location-based services

Mobile network providers have developed a variety of location-based services (LBSs), such as friend-finder, point of interest services, emergency rescue and many other safety and security services. The protection of location-privacy has consequently become a key aspect to the success of LBSs, since users consider their own physical location and movements highly privacy-sensitive, and demand for solutions able to protect such an information in a variety of environments. The idea behind location-privacy protection is that the individual should be able to set the level at which the location information is released to avoid undesired exploitation by a potential attacker: one of the approaches to this problem is given by the application of spatial obfuscation techniques, actuated by a trusted agent, and consisting in artificial perturbations of the location information collected by sensing technologies, before its disclosure to third parties. In many situations, however, landscape/map information can help a third party to perform Bayesian inference over spatially obfuscated data and to refine the user’s location estimate up to a violation of the original user’s location-privacy requirements. The goal of this paper is to provide a map-dependent obfuscation procedure that enables the release of the maximum possible user’s location information, that does not lead to a violation of the original user’s location-privacy requirements, even when refined through map-based inference.     

位置服务社交网络用户行为相似性分析

基于位置的社交网络(LBSN)能够支持用户分享地理位置信息,网站中保存用户访问真实世界地理位置的记录构成用户的行为轨迹,但LBSN用户相似性的分析并没有从用户的地理位置轨迹上加以考虑。为此,提出基于划分层次,在不同的邻域半径下密度聚类的方法,探索基于位置的服务(LBS)平台上用户地理位置上相似性的度量。该方法在不同空间位置比例尺下观察用户访问各个聚类区域的次数,进而利用向量空间模型(VSM)计算用户在各个层级的相似性,最终以不同权重叠加各层级的用户相似性值,得出用户在地理空间行为上的相似性。基于国内某大型位置社交网站真实用户数据的实验结果表明,该方法能有效识别出访问地理位置相似的用户。     

基于高效假轨迹的隐私保护算法研究

为了解决LBS服务中用户轨迹隐私泄露的问题,提出了一种基于高效假轨迹的隐私保护算法。首先,该方案综合考虑用户所处区域的背景信息,以划分网格的方式,统计每个网格的历史服务请求概率,确保生成的每一个假位置与对应真实位置具有相同的历史服务请求概率;其次,结合网格历史服务请求概率并通过万有引力定律模型计算出用户位置转移概率;最后,生成与真实位置转移概率最相近的k-1条假轨迹实现K-匿名。实验结果表明,该方案能够更有效地保护用户的轨迹隐私。     

Facilitating resource sharing and selection in ubiquitous multi-user environments

Mobile technologies have increased the interest of industry and academia in providing users with information and services anytime and anywhere. Some services are customized according to the users’ characteristics, attempting to create ubiquitous environments that enable such users to share and discover resources. However, research that addresses the creation of these environments is scant. In this article, we go further than single-user pervasive systems, by developing a support that manages shared resources in ubiquitous multi-user environments. Our contribution is a semantic matchmaking service capable of finding the most suitable resources that satisfy the users’ requirements. This service processes the users’ requests, their context, and the community participating in the resource sharing process, by respecting restrictions, the natural interaction among participants, and the changes that this interaction produces. We model the environment, shared resources, and users as dynamic entities that generate new information, which might affect the availability states of such resources. These states have been defined through the Contextual-Graphs formalism to incorporate new knowledge that can refine, extend, or customize such states, according to the users’ habits. Our matchmaking service has been deployed across the Computer Science Department of CINVESTAV-IPN research center, where it has been validated by means of several test cases.     

Complete Bipartite Anonymity for Location Privacy

Users are vulnerable to privacy risks when providing their location information to location-based services (LBS). Existing work sacrifices the quality of LBS by degrading spatial and temporal accuracy ...     

Prototyping and analysing ubiquitous computing environments using multiple layers

If ubiquitous computing (ubicomp) is to enhance physical environments then early and accurate assessment of alternative solutions will be necessary to avoid costly deployment of systems that fail to meet requirements. This paper presents APEX, a prototyping framework that combines a 3D Application Server with a behaviour modeling tool. The contribution of this framework is that it allows exhaustive analysis of the behaviour models that drive the prototype while at the same time enabling immersive exploration of a virtual environment simulating the proposed system. The development of prototypes is supported through three layers: a simulation layer (using OpenSimulator); a modelling layer (using CPN Tools) and a physical layer (using external devices and real users). APEX allows movement between these layers to analyse different features, from user experience to user behaviour. The multi layer approach makes it possible to express user behaviour in the modelling layer, provides a way to reduce the number of real users needed by adding simulated avatars, and supports user testing of hybrids of virtual and real components as well as exhaustive analysis. This paper demonstrates the approach by means of an example, placing particular emphasis on the simulation of virtual environments, low cost prototyping and the formal analysis capabilities.     

MINING USER GOALS FOR INDOOR LOCATION‐BASED SERVICES WITH LOW ENERGY AND HIGH QoS

Location‐based services (LBSs) play a very important role in pervasive computing environment, and QoS (quality of service) is one of the key evaluations for LBS. To maintain high QoS, the traditional approaches rely on accurate and continuous localization. However, the energy consumption of the mobile device under this situation is often too high for practical applications. Thus, it seems that the energy consumption and QoS become two conflicting factors in LBS systems. In this article, a new adaptive goal‐aware computing framework (Adaware) is proposed to solve this contradiction. We show that the QoS of LBS can be evaluated by recognizing user goals. We design new algorithms to mine user goals from discontinuous location data to reduce the energy consumption while keeping a high QoS at the same time. More specifically, Adaware employs an accelerometer to implement motion‐based localization, which greatly reduces the unnecessary energy consumption on Wi‐Fi scanning compared to the original continuous localization methods. Then based on the estimated discontiguous critical point traces which have been postprocessed by our proposed Localization Confident Coefficient filter method, a novel N‐gram goal inference algorithm is used to predict the accurate goal. The experimental results in real‐world wireless network environments validate the effectiveness of our framework. We can get 80% QoS under 70% location estimation accuracy within 10 meters and 30% energy saving compared to continuous Wi‐Fi scanning.     

一种基于协同矩阵分解的用户冷启动推荐算法

位置服务作为一种信息共享平台,在方便人们交流和共享信息的同时,也因为用户数量的不断增加,而面临着严重的信息过载问题.如何利用推荐技术对信息进行过滤和筛选,帮助用户在位置服务中发现有价值的信息成为近年来研究的热点.但目前已有的推荐算法,在只有消费记录这种隐性数据情况下,针对用户较少活动区域或新用户的推荐效率较低,无法最大化挖掘隐性数据所带的信息.针对以上问题,结合位置服务平台的特点,针对用户冷启动问题,提出了一种结合协同概率矩阵分解与迭代决策树(gradient boosting decision tree, GBDT)的推荐算法.该方法首先使用多层协同概率矩阵分解在多个维度上得到用户潜在特征,然后使用GBDT学习算法对特征和标签进行训练得到用户对项目的偏好,最后使用考虑约束问题的top-N推荐产生推荐列表.在真实数据集上的实验结果表明,与目前较为流行的方法相比,提出的方法能在准确率、F1值上取得较好的结果,能更好地缓解位置服务中的冷启动问题.     

基于个性化移动位置服务中自适应地图的研究

移动位置服务是一种新兴的无线增值业务,能够利用无线网络为移动用户提供基于位置的信息服务。个性化的移动位置服务是国内外研究的焦点,而自适应地图是其中最重要的方面之一。如何良好地进行地图的设计是本文研究的重点,由此提出了一种自适应地图形成模型,依据此模型可以较好地指导我们进行地图设计,进而满足移动位置服务中要求的易读性、动态性以及交互性。文章最后阐述了一种移动位置服务地图服务系统逻辑框架,并对其予以具体实现,验证了自适应地图服务系统的可行性和可用性。