Coder Social home page Coder Social logo

point-of-interest_articles's Introduction

兴趣点(POI)应用文献整理

介绍

因为这两年的研究方向是“社交媒体数据与遥感影像的联合应用”,读了一些社交媒体数据相关的文献,其中包括一部分POI应用文章。毕业论文也要用到POI数据,因此为引用方便,对近几年的POI应用文献进行了简单整理,包括应用分类和对每篇文章的内容简介。

由于未对与研究方向不相关的应用文献展开详细阅读,部分内容简介实际上是对文章摘要的整理。

目录

#1 城市场景分类

内容简介(urban scene classification))

中文 - 4篇

  • 2016 - 基于潜在语义信息的城市功能区识别——广州市浮动车GPS时空数据挖掘 - 陈世莉
  • 2016 - 基于POI数据的城市功能区定量识别及其可视化 - 池娇
  • 2018 - 基于POI 数据的城市功能区识别及主要交通枢纽空间分析
  • 2018 - 融合多源地理大数据的杭州市功能区识别和空间优化研究 - 赵智勇

英文 - 14篇

  • 2012 - Discovering Regions of Different Functions in a City Using Human Mobility and POIs
  • 2013 - Automated identification and characterization of parcels (AICP) with OpenStreetMap and Points of Interest
  • 2015 - Mapping Urban Land Use by Using Landsat Images and Open Social Data
  • 2015 - An integrative method for mapping urban land use change using “geo-sensor” data
  • 2017 - Hierarchical semantic cognition for urban functional zones with VHR satellite images and POI data - Xiuyuan Zhang
  • 2017 - Classifying urban land use by integrating remote sensing and social media data
  • 2017 - Extracting urban functional regions from points of interest and human activities on location-based social networks
  • 2017 - The Combined Use of Remote Sensing and Social Sensing Data in Fine-Grained Urban Land Use Mapping: A Case Study in Beijing, China
  • 2017 - Sensing spatial distribution of urban land use by integrating points of interest and Google Word2Vec model
  • 2018 - Social functional mapping of urban green space using remote sensing and social sensing data
  • 2018 - Beyond Word2vec: An approach for urban functional region extraction and identification by combining Place2vec and POIs
  • 2019 - Exploring semantic elements for urban scene recognition: Deep integration of high-resolution imagery and OpenStreetMap (OSM)
  • 2020 - Large-scale urban functional zone mapping by integrating remote sensing images and open social data
  • 2020 - Heuristic sample learning for complex urban scenes: Application to urban functional-zone mapping with VHR images and POI data - Xiuyuan Zhang

#2 POI推荐

内容简介(poi recommendation

中文 - 3篇

  • 2016 - LBSN中基于元路径的兴趣点推荐 - 曹玖新
  • 2017 - 基于位置社交网络的上下文感知的兴趣点推荐 - 任星怡
  • 2017 - 基于用户签到行为的兴趣点推荐 - 任星怡

英文 - 14篇

  • 2014 - Graph-based Point-of-interest Recommendation with Geographical and Temporal Influence
  • 2016 - Effective successive POI recommendation inferred with individual behavior and group preference
  • 2016 - POI Recommendation: A Temporal Matching between POI Popularity and User Regularity
  • 2017 - A temporal-aware POI recommendation system using context-aware tensor decomposition and weighted HITS
  • 2017 - CTF-ARA: An adaptive method for POI recommendation based on check-in and temporal features
  • 2018 - Analysis of user preference and expectation on shared economy platform: An examination of correlation between points of interest on Airbnb - Moloud Abdar
  • 2019 - Using POI functionality and accessibility levels for delivering personalized tourism recommendations
  • 2019 - Real-time event embedding for POI recommendation
  • 2019 - Exploiting Geographical-Temporal Awareness Attention for Next Point-of-Interest Recommendation
  • 2019 - VCG: Exploiting visual contents and geographical influence for Point-of-Interest recommendation - Zhibin Zhang
  • 2020 - Heterogeneous graph-based joint representation learning for users and POIs in location-based social network
  • 2020 - GLR: A graph-based latent representation model for successive POI recommendation
  • 2020 - Modeling hierarchical category transition for next POI recommendation with uncertain check-ins
  • 2020 - A point-of-interest suggestion algorithm in Multi-source geo-social networks - Xi Xiong

#3 城市相关指标分析

内容简介(analysis of indicators

中文 - 12篇

  • 2015 - 设施POI分布热点分析的网络核密度估计方法 - 禹文豪
  • 2016 - 基于POI数据的广州零售商业中心热点识别与业态集聚特征分析 - 陈蔚珊
  • 2016 - 基于POI数据的城市生活便利度指数研究 - 崔真真
  • 2016 - 广州市多类型商业中心识别与空间模式 - 吴康敏
  • 2016 - 利用核密度与空间自相关进行城市设施兴趣点分布热点探测 - 禹文豪
  • 2018 - 基于POI数据的城市功能区识别及主要交通枢纽空间分析
  • 2018 - 基于POI数据的长春市商业空间格局及行业分布 - 浩飞龙
  • 2019 - 基于手机定位数据的深圳市热浪人口暴露度分析
  • 2020 - 基于大数据的上海中心城区建成环境与城市活力关系分析 - 塔娜
  • 2020 - 基于POI的土地利用与轨道交通客流的空间特征 - 彭诗尧
  • 2020 - 基于POI数据的西安市零售业空间格局及影响因素研究 - 高岩辉
  • 2020 - 基于兴趣点(POI)大数据的东北城市空间结构分析 - 薛冰

英文 - 13篇

  • 2014 - Fine-resolution population mapping using OpenStreetMap points-of-interest
  • 2018 - Dynamic assessments of population exposure to urban greenspace using multi-source big data
  • 2018 - Temporal and Spatial Variation Characteristics of Catering Facilities Based on POI Data: A Case Study within 5th Ring Road in Beijing
  • 2018 - Using points-of-interest data to estimate commuting patterns in central Shanghai, China - Mengya Li
  • 2018 - Urban Impervious Surface Estimation from Remote Sensing and Social Data - Yan Yu
  • 2019 - Exploration on the spatial spillover effect of infrastructure network on urbanization: A case study in Wuhan urban agglomeration - Chen Zeng
  • 2019 - Understanding the impact of built environment on metro ridership using open source in Shanghai - Dadi An
  • 2019 - Spatiotemporal distribution characteristics and mechanism analysis of urban population density: A case of Xi'an, Shaanxi, China Jingang - Jingang Li
  • 2020 - Visualizing and exploring POI configurations of urban regions on POI-type semantic
  • 2020 - Identifying and evaluating poverty using multisource remote sensing and point of interest (POI) data: A case study of Chongqing, China
  • 2020 - Analysis on spatiotemporal urban mobility based on online car-hailing data - Bin Zhang
  • 2020 - Understanding the spatial organization of urban functions based on co-location patterns mining: A comparative analysis for 25 Chinese cities - Yimin Chen
  • 2020 - Investigating the impacts of built environment on traffic states incorporating spatial heterogeneity - Yingjiu Pan

#4 其他

内容简介(others

中文 - 3篇

  • 2011 - 利用城市POI数据提取分层地标 - 赵卫锋
  • 2012 - POI 的分类标准研究 - 张玲
  • 2015 - 核密度估计法支持下的网络空间POI点可视化与分析 - 禹文豪

英文 - 4篇

  • 2014 - A Semantic-Enhanced Augmented Reality Tool for OpenStreetMap POI Discovery - Michele Ruta
  • 2015 - Mining point-of-interest data from social networks for urban land use classification and disaggregation
  • 2019 - Land Use Regression models for 60 volatile organic compounds: Comparing Google Point of Interest (POI) and city permit data
  • 2020 - Analyzing parcel-level relationships between Luojia 1-01 nighttime light intensity and artificial surface features across Shanghai, China: A comparison with NPP-VIIRS data

交流邮箱:[email protected]

point-of-interest_articles's People

Contributors

hauwong avatar

Stargazers

Hongcheng Jia avatar Classic C avatar  avatar  avatar Zhenbai avatar  avatar Li Yongkang avatar  avatar Syke_h avatar

Watchers

 avatar

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. 📊📈🎉

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google ❤️ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.