Research

Statistical learning methods, and the applied problems that motivate them.

Research of Luca Frigau: clustering, decision trees and classification, text mining and topic modeling, heaped counts and GAITD regression, statistical image analysis and applied statistics.

My research develops statistical learning methods that are interpretable and computationally efficient, often together with colleagues who bring the data and the questions. Each of the five lines of work below has a story that tells how it developed. The stories distinguish the methods developed with my colleagues, such as NeSSC, TORS and PARSEG, from existing methods, such as topic models and GAITD regression, that we applied to new problems. Other topics and funded projects follow. The Publications page shows how these lines developed over time, with the complete list of works.

From methods to real-world problems

The methods of the five lines below have been applied in many fields, from tourism and transport to health and botany. The diagram is drawn from the publications of each line.

  • Cultural heritage
  • Tourism
  • Transport and logistics
  • Insurance
  • Higher education
  • Marketing and social media
  • Scientific conferences
  • Health
  • Botany
Each curve joins a research line to a field in which at least one of its publications applies its methods. The research lines link to their stories.
Publications behind each curve
Cultural heritage
Clustering: Comparison of Cluster Analysis Approaches for Binary Data (2018)
Trees and classification: Near-Infrared Spectroscopy and Machine Learning for Accurate Dating of Historical Books (2023); Machine learning and NIR spectroscopy for dating of books (2023)
Tourism
Clustering: Semi-Supervised Sentiment Clustering on Natural Language Texts (2023)
Trees and classification: Application of machine learning models to discriminate tourist landscapes using eye-tracking data (2021); Territorial Determinants of Tourist Arrivals: A Multivariate Regression Tree Analysis (2026); Multivariate Regression Trees for the Analysis of Socio-Economic Phenomena: Evidence from Tourism and Health Outcomes (2026)
Text mining: Customer Satisfaction from Booking (2019); Gauging Airbnb Review Sentiments and Critical Key-Topics by Small Area Estimation (2024); From Self-Perception to Feedback: Mapping Sustainability-Oriented Self-Descriptions to Airbnb Reviews (2025)
Transport and logistics
Clustering: A new management scheme to support reverse logistics processes in the agrifood distribution sector (2017); Investigating the Role of the Human Element in Maritime Accidents using Semi-Supervised Hierarchical Methods (2021)
Trees and classification: Delay prediction in container terminals: A comparison of machine learning methods (2013); A data mining approach to forecast late arrivals in a transhipment container terminal (2014)
Text mining: Exploring Spatial Disparities and Gaps in Transportation and Mobility through Airbnb Reviews: A Sardinian Case Study (2025)
Insurance
Trees and classification: The SASSC Algorithm: an Application to Insurance Data (2017)
Higher education
Trees and classification: Feature-Selective Oblique Trees for Regression: Application to STEM Graduate Wage Prediction in Italy (2025)
Text mining: Explaining Student Satisfaction Assessments: A Natural Language Processing Approach (2022); Topic Based Quality Indexes Assessment Through Sentiment (2024)
Marketing and social media
Text mining: Value Co-Destruction: a Text-Mining-Based Mixed Method Study on Social Media Interactions (2019); How emotions impact the interactive value formation process during problematic social media interactions (2023); Value Co-creation or Value Co-destruction? The Role of Negative Emotions in Consumer-Firm Interaction in the Social Media Platform (2023)
Scientific conferences
Text mining: Optimizing the JSM Program (2022); Optimizing time slots in scientific meetings: a Latent Dirichlet allocation approach (2022); Enhancing Time Slot Efficiency in Scientific Conferences by Employing Latent Dirichlet Allocation (2024)
Health
Trees and classification: Health Care Fraud Classifiers in Practice (2021); Multivariate Regression Tree to Investigate the Italian Mortality Rates (2023); Multivariate Regression Trees for the Analysis of Socio-Economic Phenomena: Evidence from Tourism and Health Outcomes (2026)
Count models: Heaping and seeping, GAITD regression and doubly constrained reduced rank vector generalized linear models, in smoking studies (2024); Heaping and seeping, GAITD regression and doubly constrained reduced-rank vector generalized linear models, in smoking studies (2025)
Botany
Image analysis: Classification of Images Background Subtraction in Image Segmentation (2016); Validating image segmentation of botanical seeds (2016); Validation of Experiments Involving Image Segmentation of Botanic Seeds (2017); Comparison of Non-parametric Approaches in Classification of Seeds (2018); A statistical approach to the morphological classification of Prunus sp. seeds (2020); PARSEG: A computationally efficient approach for statistical validation of botanical seeds’ images (2024)

Research stories

  • Clustering

    How do we find groups in data that we can trust?

    Methods to find groups of similar observations, also with the help of an outcome variable, and to validate partitions and choose between clustering methods.

  • Decision trees and classification

    How can a prediction rule be both reliable and easy to read?

    From the reliability of classifiers and their use on real problems to oblique regression trees, which split the data with hyperplanes and remain easy to read.

  • Text mining and topic modeling

    What can statistics learn from what people write?

    Topic models and sentiment analysis turn reviews, course evaluations and conference programs into data, and can help to schedule a better conference.

  • Counts and rounded answers

    What do rounded answers hide?

    Self-reported counts pile up on round numbers. We modeled these spikes, instead of ignoring them, to study the age at which people start smoking.

  • Statistical image analysis

    How can we get reliable information from images?

    Images of seeds, from segmentation and classification to validation: PARSEG validates a segmentation with a small sample of its pixels, with roughly the same precision.

Other topics

Collaborative work outside the five lines above. Most of it falls into a few groups:

  • Clinical and health research, above all the Italian adaptation and validation of questionnaires used in rehabilitation medicine, with studies in orthopaedics, dentistry and neuroimaging.
  • Tourism and the sharing economy, including regression models (ordinal, logit and probit) of the prices and performance of Airbnb accommodation and of the Superhost status of hosts, and the online communication of heritage sites.
  • Eye tracking and Markov chains, to study web usability and how tourists look at landscapes and move across Sardinia.
  • Plant biology: seed germination and alien plants in wetlands.

Single studies concern risk analysis, experimental economics, scientometrics, student mobility and graduate wages. Applied work that uses the methods of the five lines is listed with them.

  • clinical research
  • tourism
  • ordinal regression
  • eye tracking
  • plant biology

Selected work

Funded projects

Principal investigator and scientific coordinator

  • Clustering in non-Euclidean spaces: theoretical foundations and alternative approaches. Principal investigator. Fondazione di Sardegna, call for basic research projects 2025.
  • HEALTH-GUARD: analysis of the environmental, economic and social sustainability impacts of the processes studied in the LucAS project. Scientific coordinator for the University of Cagliari. Part of the project LucAS – Lucani tra Ambiente e Salute, funded by the Basilicata Region.
  • The role of advanced statistics in the co-planning of interventions supporting non-self-sufficiency. Scientific coordinator. Funded by the Italian National Social Security Institute (INPS), call of 15 July 2020.

Research units

I am or have been a senior member of the University of Cagliari units of national and regional projects, including RISING (National Programme for Research, Innovation and Competitiveness 2021–2027), e.INS – Ecosystem of Innovation for Next Generation Sardinia and GRINS – Growing Resilient, Inclusive and Sustainable (National Recovery and Resilience Plan), and projects funded by the Ministry of University and Research, the Fondazione di Sardegna, the Autonomous Region of Sardinia and the Ethereum Foundation.