Computing least air pollution exposure routes

Personalized routing counts on traveler’s preferences which are usually based on different criteria, such as shortest, fastest, least traffic, or less expensive (e.g., less fuel cost, toll free). However, people are increasingly becoming concerned about the adverse health effects of exposure to air pollution in chosen routes. Exposures to elevated air pollution concentrations particularly endanger children, pregnant women, elderly people, and people with asthma and other respiratory conditions. Choosing routes with least air pollution exposure (APE) is seen as one approach to minimize the level of pollution exposed, which is a major public health issue. Routing algorithms use weights on segments of road networks to find optimum routes. While existing weights are commonly distance and time, among a few others, there is currently no weight based on APE to compute least APE routes. In this paper, we present a weight function that computes weight based on APE. Two different approaches, geostatistical and non-geostatistical, were used to compute APE weight. Each approach was evaluated, and the results indicate that the APE weight is suitable for computing least APE routes.     

浅析个性化地图

近来,个性化地图以其独特的形式语言和丰富的人文内涵受到越来越多用户的喜爱和认可,也有越来越多的人参与到个性化地图的设计中。由此,通过对个性化地图发展现状的总结,以及对个性化地图概念、特点和分类的梳理,可为今后个性化地图的设计和研究提供一些参考与帮助。     

基于Item2Vec负采样优化的专题地图产品个性化推荐方法研究

建立适用于专题地图产品检索的用户偏好推荐模型是提高专题地图质量的有效方式之一,在专题地图产品推荐场景中,存在严重的内容冷启动和评论数据稀疏问题,现有的推荐算法无法为特定类用户推荐不同特征的专题地图产品,导致用户从专题地图中获取偏好信息受到限制。因此,本文构建基于负采样的连续词袋模型和基于Word2Vec的Item2Vec相结合的用户偏好推荐方法,用于专题地图产品推荐。① 计算用户行为日志文件中交互行为数据的隐性评分,以代替专题地图推荐信息流场景中稀疏的用户评论数据;② 基于负采样的连续词袋模型提取目标专题地图的前后地图序列感知特征信息,通过控制正负样本比例为1:2,提升目标专题地图潜在评分的预测精度;③ 通过Item2Vec将带有用户行为特征信息的专题地图映射到向量空间,计算用户对专题地图的相似度矩阵,根据用户偏好程度完成推荐。在构建的专题地图评分实验数据集Thematic CMaps和4个公开验证数据集MovieLens上的测试结果表明:与LFM、Personal Rank、Content Based和SVD 4种传统推荐算法相比,本文所提方法可有效提高潜在评分的预测精度,推荐性能最高达到27.85%;与以霍夫曼采样方式的Item2Vec基础方法和YouTubeNet 2种神经网络推荐算法相比,评分预测精度有一定提高,且推荐性能不断提升,最高达到2.97%和5.78%。以经典算法奇异值分解（SVD）为例,将MovieLens-20M数据集切分后,在数据量不断增大的数据子集中,本文所用方法的评分预测精度和性能均优于SVD方法。     

基于改进混合蛙跳算法的个性化旅游路线推荐

大众在旅游途中期望获得开销低、行程方便、舒适度高的旅游体验,同时还具有历史人文、自然景观、美食购物等不同游览需求.因此,本文提出了一种基于改进混合蛙跳算法的个性化旅游路线推荐方法.首先建立个性化旅游路线推荐问题的优化模型,并针对该模型的特点,设计改进混合蛙跳算法.通过调整可控精度,增加筛选准则和及时处理异常解等策略增强群体的多样性,降低遗漏最优解的风险,强化局部搜索能力,并提高算法的求解精度.以南京三日游个性化旅游路线推荐问题作为实例,收集南京市内知名景点的门票价格、开放时间、不同出行方式所需的时间和花费情况以及食宿费用等相关数据,基于改进混合蛙跳算法进行求解.实验结果表明,与改进前的方法相比,所提改进方法能够获取更优的路径解,推荐的路线能够更好地满足用户的个性需求.     

Constructing personalized transportation networks in multi-state supernetworks: a heuristic approach

An integrated view encompassing the networks for public and private transport modes as well as the activity programs of travelers is essential for accessibility analysis. In earlier research, the multi-state supernetwork has been put forward by the authors as a suitable technique to model the system in such an integrated fashion. An essential part of a supernetwork involving multi-modal and multi-activity is the personalized transportation network, which is an under-researched topic in the academic community. This article attempts to develop a heuristic approach to construct personalized transportation networks for an individual's activity program. In this approach, the personalized network consists of two types of network extractions from the original transportation system: public transport network and private vehicle network. Three examples are presented to illustrate that the public transport network and private vehicle network can represent an individual's attributes and be applied in large-scale applications for analyzing the synchronization of land-use and transportation systems.     

LBS中位置及其语义的研究

阐述了两种LBS位置表示方法，引入了语义位置的概念，对现有的语义位置概念作了修正。强调了位置属性也是语义位置的重要组成部分。通过对位置概念内涵和外延的分析，讨论了位置属性所包括的内容；运用层次建模，实现了位置之间关系的描述。为了能够规范化地描述语义位置，运用本体技术，对位置所包含的语义信息进行了描述，建立了能够被计算机识别和处理的OWI。位置本体模型。通过对语义位置的本体建模，实现了位置信息的知识化描述，为实现个性化服务奠定了基础。     

旅游饭店个性化服务探讨

文章从国内外旅游饭店服务发展的简要历程、规范服务与个性服务的辩证关系,透视了旅游饭店个性化服务的内涵实质,并从不同的角度和层次划分出了几种服务类型。归纳出旅游饭店个性化服务包括灵活服务与超常服务、主动服务与超前服务、细节服务与超值服务、情感服务与特色服务等类型,概括出旅游饭店个性化服务具有多样性、意外性、开拓性以及风险性等特征。     

Web 2.0环境下测绘实践个性化平台的构建

随着教育信息化的快速发展,网络个性化学习越来越普遍。提升大学生的网络学习能力成为一个重要的研究课题。本文结合Web 2.0技术的特点和优势,以学生学习的个性化、自主性为基础,以测绘专业实践教学改革为依托,探讨了利用Web 2.0技术进行个性化学习测绘实践教学平台建设的意义、可行性和技术路线。     

LBS中基于轨迹的用户行为特征分析

LBS的发展趋势是向用户提供智能化、个性化的位置服务。以用户行为轨迹数据为基础,进行轨迹简化、POI匹配、时空融合、习惯分析等处理,建立起用户行为特征模型,从而实现向不同用户提供个性化位置服务。