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Large language models (LLMs) are advancing rapidly. Such models have demonstrated strong capabilities in learning from large-scale (unstructured) text data and answering user queries. Users do not need to be experts in structured query languages to ...

Geotagged Social Media (GTSM) data, especially geotagged tweets are valuable sources of information for many important applications. Only small portions of geotagged tweets are available (less than 3%). Identifying tweet location is a challenging ...

Selecting the best items in a dataset is a common task in data exploration. However, the concept of “best” lies in the eyes of the beholder: Different users may consider different attributes more important and, hence, arrive at different rankings. ...

COVID-19 has brought about substantial social, economic and health related burdens, motivating different control measures from policy makers worldwide. Contact tracing plays a pivotal role in the COVID-19 era. However, contact tracing is by nature ...

Utility systems such as electric, fiber/telco, gas, and water require the realistic modeling of network attributes or values over distance. For example, consider hydraulic pressure in a pipe network; as water flows away from the reservoir or pump, ...

Several industries rely on accurate and efficient processing of 3D spatial queries over increasingly large datasets for decision optimization and exploration purposes. Examples include clinical diagnosis supported by 3D imaging of human tissues, ...

Applications based on spatial data has become present in our daily lives. Spatial data can be used to represent objects such as roads, bus stops, restaurants and schools. Some of these objects maybe associated with a text (e.g. menu of a restaurant). ...

In recent years, ridesharing has become a popular model that enables users to share their rides with others. In this article, we introduce a novel ridesharing service, an Activity-aware Ridesharing Group Trip Planning (ARGTP) query, in road networks ...

In its current form, ride-sharing is responsible for a small fraction of traffic load compared to other transportation modes, especially private vehicles. As its benefits became more evident, and obstacles, e.g., lack of liability legislation, that may ...

Road network map is one of the datasets that are used in many different applications. Many smart cities have more than one Road Network map from different sources (government authorities, private enterprise, or volunteered). Be that as it may, there is ...

Widespread use of advanced mobile devices has led to the emergence of a new class of crowdsourcing called spatial crowdsourcing. Spatial crowdsourcing advances the potential of a crowd to perform tasks related to real-world scenarios involving physical ...

Activity-Based ride-sharing is a new paradigm which enhances the current model based on fixed origins and destinations, namely trip-based ride-sharing. In this new model, a user issues a ride-sharing request with his origin and the activity he wants to ...

Given a utility network and one or more starting points that define where analysis should begin, the problem of analyzing utility networks entails assembling a subset of network elements that meet some specified criteria. Analyzing utility network data ...

Route planning for a set of locations based on trajectory searching is a hot topic. To obtain previous drivers' knowledge on route selection, some existing works search trajectories which are spatially close to the query locations. However, these ...

Recent advancements in data mining coupled with the ubiquity of mobile devices has led to the possibility of mining for events in real-time. We introduce the problem of mining for an individual's encounters. As people travel, they may have encounters ...

Recently, an understanding of mass movement in urban areas immediately after large disasters, such as the Great East Japan Earthquake (GEJE), has been needed. In particular, mobile phone data is available as time-varying data. However, much more ...

With the deployment of modern infrastructures for public transit, several studies have analyzed the transition patterns of people by using smart card data and have characterized the areas. In this paper, we propose a novel embedding method to obtain a ...

Owing to the recent development of mobile computing and communication network technologies, efficiently retrieving relevant data from a huge spatial database has become more and more important. In this paper, we study a practical and novel problem of ...

Major navigation companies have resorted to crowdsourcing for obtaining traffic data to improve their services. In fact, a new generation of navigation systems are emerging for the sole purpose of connecting drivers on the road (Waze.com) so that they ...

The need to store vast amounts of trajectory data becomes more problematic as GPS-based tracking devices become increasingly prevalent. There are two commonly used approaches for compressing trajectory data. The first is the line generalisation approach ...