From Data to Models and Back
9th International Symposium, DataMod 2020, Virtual Event, October 20, 2020, Revised Selected Papers
Page
%P
-
Chapter and Conference Paper
Interpretable Data Partitioning Through Tree-Based Clustering Methods
The growing interpretable machine learning research field is mainly focusing on the explanation of supervised approaches. However, also unsupervised approaches might benefit from considering interpretability a...
-
Chapter and Conference Paper
Geolet: An Interpretable Model for Trajectory Classification
The large and diverse availability of mobility data enables the development of predictive models capable of recognizing various types of movements. Through a variety of GPS devices, any moving entity, animal, ...
-
Article
City indicators for geographical transfer learning: an application to crash prediction
The massive and increasing availability of mobility data enables the study and the prediction of human mobility behavior and activities at various levels. In this paper, we tackle the problem of predicting the...
-
Article
Gross polluters and vehicle emissions reduction
Vehicle emissions produce an important share of a city’s air pollution, with a substantial impact on the environment and human health. Traditional emission estimation methods use remote sensing stations, missi...
-
Article
Open AccessIndividual and collective stop-based adaptive trajectory segmentation
Identifying the portions of trajectory data where movement ends and a significant stop starts is a basic, yet fundamental task that can affect the quality of any mobility analytics process. Most of the many ex...
-
Chapter and Conference Paper
Explaining Crash Predictions on Multivariate Time Series Data
In Assicurazioni Generali, an automatic decision-making model is used to check real-time multivariate time series and alert if a car crash happened. In such a way, a Generali operator can call the customer to ...
-
Article
Open AccessGive more data, awareness and control to individual citizens, and they will help COVID-19 containment
The rapid dynamics of COVID-19 calls for quick and effective tracking of virus transmission chains and early detection of outbreaks, especially in the “phase 2” of the pandemic, when lockdown and other restric...
-
Book and Conference Proceedings
-
Chapter
Visual Analytics for Characterizing Mobility Aspects of Urban Context
Visual analytics science develops principles and methods for efficient human–computer collaboration in solving complex problems. Visual and interactive techniques are used to create conditions in which human a...
-
Chapter and Conference Paper
Measuring Immigrants Adoption of Natives Shop** Consumption with Machine Learning
“Tell me what you eat and I will tell you what you are”. Jean Anthelme Brillat-Savarin was among the firsts to recognize the relationship between identity and food consumption. Food adoption choices are much l...
-
Article
Car telematics big data analytics for insurance and innovative mobility services
Car telematics is a large and growing business sector aiming to collect mobility-related data (mainly private and commercial vehicles) and to develop services of various nature both for individual citizens and...
-
Chapter and Conference Paper
Discovering Tourist Attractions of Cities Using Flickr and OpenStreetMap Data
Tourism is a growing industry which needs accurate management and planning. Photography and tourism are inseparable; Photographs play the role of tourists’ footprints during their visit to a touristic city. No...
-
Chapter and Conference Paper
Advancements in Mobility Data Analysis
Some recent advancements in the area of Mobility Data are discussed, a field in which data mining and machine learning methods are applied to infer descriptive patterns and predictive models from digital tra...
-
Chapter and Conference Paper
Discovering Mobility Functional Areas: A Mobility Data Analysis Approach
do we the of and are the functional units of the territory? Nowadays, we typically do that just looking at census data, while in this work we aim to identify functional areas for mobility in a...
-
Article
Scalable and flexible clustering solutions for mobile phone-based population indicators
Mobile phones have an unprecedented rate of penetration across the world. Such devices produce a large amount of data that have been used on different domains. In this work, we make use of mobile calls to moni...
-
Chapter and Conference Paper
Movement Behaviour Recognition for Water Activities
This work describes an analysis process for the movement traces of users during water activities. The data is collected by a mobile phone app that the Navionics company developed to provide to its users sea ma...
-
Article
Guest editors’ introduction to the EcmlPkdd 2016 journal track special issue of Machine Learning
-
Article
Guest editors’ introduction to the EcmlPkdd 2016 journal track special issue of Machine Learning
-
Chapter
The Inductive Constraint Programming Loop
Constraint programming is used for a variety of real-world optimization problems, such as planning, scheduling and resource allocation problems. At the same time, one continuously gathers vast amounts of data ...
-
Chapter
Partition-Based Clustering Using Constraint Optimization
Partition-based clustering is the task of partitioning a dataset in a number of groups of examples, such that examples in each group are similar to each other. Many criteria for what constitutes a good cluster...
