Jie Bao

• Doctor of Philosophy
• Researcher at Microsoft

Unregistered illegal facilities that do not qualify for chemical production pose substantial threats to human lives and the environment. For human safety and environmental protection, the government needs to figure out the illegal facilities and shut them down. A new, convenient, and affordable approach to detect such facilities is to analyze the t...

Government collaboration tasks are integral for grassroots governance and essential for government administration. Large-scale government collaboration tasks often involve multiple departments working together to solve complex tasks that require handling large amounts of data. However, existing offline processes make it difficult to manage complex...

The updated residential-level fine-grained digital map is essential for last-mile delivery. However, many of those low-level roads are not recorded in maps due to the high mapping costs. With the digitization of the logistics industry, couriers’ trajectories become a promising data source to complete missing roads in maps. Existing trajectory-based...

The rapid development of positioning technology produces an extremely large volume of spatio-temporal data with various geometry types such as point, line string, polygon, or a mixed combination of them. As one of the most fundamental but time-consuming operations, $k$ nearest neighbors join ( $k$ NN join) has attracted much attention. However,...

Intelligent logistics relies on accurately predicting the service time, which is a part of time cost in the last-mile delivery. However, service time prediction (STP) is non-trivial given complex delivery circumstances, location heterogeneity, and skewed observations in space, which are not well-handled by existing solutions. In our prior work, we...

Illegal vehicle parking is a common urban problem faced by major cities, as it incurs traffic jams, which lead to air pollution and traffic accidents. The government highly relies on active human efforts to detect illegal parking events. However, such an approach is extremely ineffective to cover a large city since the police have to patrol over th...

With the rapid development of the Internet of Things (IoT), massive trajectories have been generated. Trajectory data is beneficial for many urban applications. This demo presents a holistic trajectory data management system based on distributed platforms, such as Spark and HBase, namely JUST-Traj. It provides a variety of indexes to efficiently su...

Illegal vehicle parking is a common urban problem faced by major cities in the world, as it incurs traffic jams, which lead to air pollution and traffic accidents. The government highly relies on active human efforts to detect illegal parking events. However, such an approach is extremely ineffective to cover a large city since the police have to p...

The spatial time series generated by city sensors allow us to observe urban phenomena like environmental pollution and traffic congestion at an unprecedented scale. However, recovering causal relations from these observations to explain the sources of urban phenomena remains a challenging task because these causal relations tend to be time-varying...

People often refer to a place of interest (POI) by an alias. In e-commerce scenarios, the POI alias problem affects the quality of the delivery address of online orders, bringing substantial challenges to intelligent logistics systems and market decision-making. Labeling the aliases of POIs involves heavy human labor, which is inefficient and expen...

Nowadays, couriers are still the main solution to address the “last mile” problem in logistics. They are usually required to record the delivery time of each parcel manually, which is essential for delivery insurances, delivery performance evaluations, and customer available time discovery. Stay points extracted from couriers’ trajectories provide...

With the development of positioning technology, a large number of trajectories have been generated, which are very useful for many urban applications. However, it is challenging to manage trajectory data for its spatio-temporal dynamics and high-volume properties. Existing trajectory data management frameworks suffer from efficiency or scalability...

Many spatiotemporal events can be viewed as contagions. These events implicitly propagate across space and time by following cascading patterns, expanding their influence, and generating event cascades that involve multiple locations. Analyzing such cascading processes presents valuable implications in various urban applications, such as traffic pl...

Bus routes are typically updated every 3-5 years to meet constantly changing travel demands. However, identifying deficient bus routes and finding their optimal replacements remain challenging due to the difficulties in analyzing a complex bus network and the large solution space comprising alternative routes. Most of the automated approaches canno...

Discovering real-time reachable areas of a specified location is of importance for many location-based applications. The real-time reachable area of given location changes with different environments. Existing methods fail to capture real-time traffic conditions instantly. This paper provides the first attempt to discover real-time reachable areas...

Bus routes are typically updated every 3-5 years to meet constantly changing travel demands. However, identifying deficient bus routes and finding their optimal replacements remain challenging due to the difficulties in analyzing a complex bus network and the large solution space comprising alternative routes. Most of the automated approaches canno...

With the rapid development of sensing technologies, massive spatiotemporal data have been acquired from the urban space with respect to different domains, such as transportation and environment. Numerous co-occurrence patterns (e.g., traffic speed < 10km/h, weather = foggy, and air quality = unhealthy) between the transportation data and other type...

Virus transmission from person to person is an emergency event facing the global public. Early detection and isolation of potentially susceptible crowds can effectively control the epidemic of its disease. Existing metrics can not correctly address the infected rate on trajectories. To solve this problem, we propose a novel spatio-temporal infected...

Accurate and updated road network data is vital in many urban applications, such as car-sharing, and logistics. The traditional approach to identifying the road network, i.e., field survey, requires a significant amount of time and effort. With the wide usage of GPS embedded devices, a huge amount of trajectory data has been generated by different...

The objective of public resource allocation, e.g., the deployment of billboards, surveillance cameras, base stations, trash bins, is to serve more people. However, due to the dynamics of human mobility patterns, people are distributed unevenly on the spatial and temporal domains. As a result, in many cases, redundant resources have to be deployed t...

Planning ideal transit routes in the complex urban environment can improve the performance and efficiency of public transportation systems effectively. However, finding such routes is computationally difficult due to the huge solution space constituted by billions of possible routes. Considering the limited scalability of exact search methods, heur...

Given a set of user-specified locations and a massive trajectory dataset, the task of mining spatio-temporal reachable regions aims at finding which road segments are reachable from these locations within a given temporal period based on the historical trajectories. Determining such spatio-temporal reachable regions with high accuracy is vital for...

Bike-sharing systems become more and more popular in the urban transportation system, because of their convenience in recent years. However, due to the high daily usage and lack of effective maintenance, the number of bikes in good condition decreases significantly, and vast piles of broken bikes appear in many big cities. As a result, it is more d...

Air pollution has become a serious public health problem for many cities around the world. To find the causes of air pollution, the propagation processes of air pollutants must be studied at a large spatial scale. However, the complex and dynamic wind fields lead to highly uncertain pollutant transportation. The state-of-the-art data mining approac...

Trajectory data has been widely used in many urban applications. Sharing trajectory data with effective supervision is a vital task, as it contains private information of moving objects. However, malicious data users can modify trajectories in various ways to avoid data distribution tracking by the hashing-based data signatures, e.g., MD5. Moreover...

Many real-world human behaviors can be characterized as a sequential decision making processes, such as urban travelers choices of transport modes and routes (Wu et al. 2017). Differing from choices controlled by machines, which in general follows perfect rationality to adopt the policy with the highest reward, studies have revealed that human agen...

Cycling as a green transportation mode has been promoted by many governments all over the world. As a result, constructing effective bike lanes has become a crucial task to promote the cycling life style, as well-planned bike lanes can reduce traffic congestions and safety risks. Unfortunately, existing trajectory mining approaches for bike lane pl...

A path query aims to find trajectories passing a given sequence of connected road segments within a time period. It is very useful in many urban applications: 1) traffic modeling, 2) frequent path mining, 3) intersection coordination, and 4) traffic anomaly detection. Existing solutions for path query processing are implemented based on single mach...

Illegal vehicle parking is a common urban problem faced by major cities in the world, as it incurs traffic jams, which lead to air pollution and traffic accidents. Traditional approaches to detect illegal vehicle parking events rely highly on active human efforts, e.g., police patrols or surveillance cameras. However, these approaches are extremely...

Finding an ideal home is a difficult and laborious process. One of the most crucial factors in this process is the reachability between the home location and the concerned points of interest, such as places of work and recreational facilities. However, such importance is unrecognized in the extant real estate systems. By characterizing user require...

With the rapid development of location-acquisition techniques, massive trajectories are continuously generated. Many urban applications rely heavily on the data mining/analysis results of massive trajectory data. This demo presents a holistic data management system for both historical and real-time trajectory records based on a cloud platform, such...

A path query aims to find the trajectories that pass a given sequence of connected road segments within a time period. It is very useful in many urban applications, e.g., 1) traffic modeling, 2) frequent path mining, and 3) traffic anomaly detection. Existing solutions for path query are implemented based on single machines, which are not efficient...

Cycling as a green transportation mode has been promoted by many governments all over the world. As a result, constructing effective bike lanes has become a crucial task for governments promoting the cycling life style, as well-planned bike paths can reduce traffic congestion and decrease safety risks for both cyclists and motor vehicle drivers. Un...

Mining the most influential location set finds $k$ locations, traversed by the maximum number of unique trajectories, in a given spatial region. These influential locations are valuable for resource allocation applications, such as selecting charging stations for electric automobiles and suggesting locations for placing billboards. This problem is...

Mining the most influential k-location set finds k locations, traversed by the maximum number of unique trajectories, in a given spatial region. These influential locations are valuable for resource allocation applications, such as selecting charging stations for electric automobiles and suggesting locations for placing billboards. This problem is...

With advances in location-acquisition techniques, such as GPS- embedded phones, an enormous volume of trajectory data is generated, by people, vehicles, and animals. This trajectory data is one of the most important data sources in many urban computing applications, e.g., traffic modeling, user profiling analysis, air quality inference, and resourc...

More and more geo-tagged social media data is generated, nowadays, from the geo-tagged tweets, geo-tagged photos to check-ins. Analyzing this flourish data enables the possibility for us to discover users daily mobility patterns, profiles and preferences. As a result, based on the analyzed results, new types of location-based services emerge. In th...

The problem of formulating solutions immediately and comparing them rapidly for billboard placements has plagued advertising planners for a long time, owing to the lack of efficient tools for in-depth analyses to make informed decisions. In this study, we attempt to employ visual analytics that combines the state-of-the-art mining and visualization...

Recent advances in localization techniques have fundamentally enhanced social networking services, allowing users to share their locations and location-related contents, such as geo-tagged photos and notes. We refer to these social networks as location-based social networks (LBSNs). Location data bridges the gap between the physical and digital wor...

Predictive queries on moving objects offer an important category of location-aware services based on the objects' expected future locations. A wide range of applications utilize this type of services, e.g., traffic management systems, location-based advertising, and ride sharing systems. This paper proposes a novel index structure, named Predictive...

Context represents any information that can be used to characterize the situation of an entity. An entity is a person, place, or object that is considered relevant to the interaction between a user and an application, including the user and application themselves. The ubiquity of mobile devices (e.g., smartphones, GPS devices) has in part motivated...

As a result of significantly growing competition from online-only retailers, physical store retailers have resorted to measures such as discount coupons, online price matching, sale events, and a seamless omnichannel customer experience. One important, often overlooked method is partner-marketing, where a retailer promotes products or services offe...

Location based social networks (LBSNs) are becoming increasingly popular with the fast deployment of broadband mobile networks and the growing prevalence of versatile mobile devices. This success has attracted great interest in studying and measuring the characteristics of LBSNs, such as Facebook Places, Yelp, and Google+ Local. However, it is ofte...

This demo presents Minnesota Traffic Generator (MNTG); an extensible web-based road network traffic generator. MNTG enables its users to generate traffic data at any arbitrary road networks with different traffic generators. Unlike existing traffic generators that require a lot of time/effort to install, configure, and run, MNTG is a web service wi...

The 21st ACM SIGSPATIAL Conference on Advances in Geographic Information Systems (GIS) was held in November of 2013 in Orlando, Florida. Following the success of last year's event, we organized the second programming contest associated with the conference, called the SIGSPATIAL GIS Cup 2013. The subject of the competition was Geo-fencing, which ide...

News feed function becomes very popular in many social networking services and news aggregators, as it delivers the messages from users' subscribed sources. More recently, location has been introduced to the news feed function, which returns the news items relevant to the user's location. However, with the large number of the news items generated b...

This demo presents the iRoad framework for evaluating predictive queries on moving objects for road networks. The main promise of the iRoad system is to support a variety of common predictive queries including predictive point query, predictive range query, predictive KNN query, and predictive aggregate query. The iRoad framework is equipped with a...

Road network traffic datasets have attracted significant attention in the past decade. For instance, in spatio-temporal databases area, researchers harness road network traffic data to evaluate and validate their research. Collecting real traffic datasets is tedious as it usually takes a significant amount of time and effort. Alternatively, many re...

In this paper, we provide a detailed analysis on the venue popularity in Foursquare, a leading location-based social network. By collecting 2.4 million venues from 14 geographic regions all over the world, we study the common characteristics of popular venues, and make the following observations. First, venues with more complete profile information...

Location based social networks (LBSNs) are becoming increasingly popular with the fast deployment of broadband mobile networks and the growing prevalence of versatile mobile devices. This success has attracted great interest in studying and measuring the characteristics of LBSNs. However, it is often prohibitive, and sometimes impossible, to obtain...

The popularity of location-based social networks provide us with a new platform to understand users' preferences based on their location histories. In this paper, we present a location-based and preference-aware recommender system that offers a particular user a set of venues (such as restaurants) within a geospatial range with the consideration of...

This paper features Sindbad; a location-based social networking system. Sindbad supports three new services beyond traditional social networking services, namely, location-aware news feed, location-aware recommender, and location-aware ranking. These new services not only consider social relevance for its users, but they also consider spatial relev...

This demo presents Sindbad; a location-based social networking system. Sindbad supports three new services beyond traditional social networking services, namely, location-aware news feed, location-aware recommender, and location-aware ranking. These new services not only consider social relevance for its users, but they also consider spatial releva...

This paper presents the Geo Feed system, a location-aware news feed system that provides a new platform for its users to get spatially related message updates from either their friends or favorite news sources. Geo Feed distinguishes itself from all existing news feed systems in that it takes into account the spatial extents of messages and user lo...

Many social networks, e.g., Slashdot and Twitter, can be represented as directed graphs (digraphs) with two types of links between entities: mutual (bi-directional) and one-way (uni-directional) connections. Social science theories reveal that mutual connections are more stable than one-way connections, and one-way connections exhibit various tende...

Recently, several techniques have been proposed to protect the user location privacy for location-based services in the Euclidean space. Applying these techniques directly to the road network environment would lead to privacy leakage and inefficient query processing. In this paper, we propose a new location anonymization algorithm that is designed...

Social networking applications have become very important web services that provide Internet-based platforms for their users to interact with their friends. With the advances in the location-aware hardware and software technologies, location-based social networking applications have been proposed to provide services for their users, taking into acc...

A k-Range Nearest Neighbor (or kRNN for short) query in road networks finds the k nearest neighbors of every point on the road segments within a given query region based on the network distance. The kRNN query is significantly important for location-based applications in many realistic scenarios. For example, (1) the user's location is uncertain, i...

The k-anonymity technique is widely used to provide location privacy protection for accessing location-based services (LBS), i.e., the exact location of a query initiator is cloaked into a spatial region that contains at least k indistinguishable users. However, a centralized location anonymizer may pose serious privacy threats and could be the sys...

The k-anonymity technique is widely used to provide location pri- vacy protection for accessing location-based services (LBS), i.e., the exact location of a query initiator is cloaked into a spatial region that contains at least k indistinguishable users. However, a cen- tralized location anonymizer may pose serious privacy threats and could be the...

In order to access location-based services, mobile users have to disclose their exact locations to service providers. However, adversaries could collect the location information for purposes against mobile users' privacy. There are existing solutions for privacy protection by utilizing the K-anonymity model. However, the computational and communica...

The wide increase of web-based user-generated content and social networking technologies have led to the wide popularity of the term Web 2.0, in which the World Wide Web has moved from being an interface for information retrieval to an interactive medium. Fol-lowing Web 2.0, a flurry of 2.0s have appeared including Library 2.0, Travel 2.0, Governme...