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Machine Learning for Criminology and Crime Research reviews the roots of the intersection between machine learning, Artificial Intelligence, and research on crime, examines the current state of the art in this area of scholarly inquiry, and discusses future perspectives that may emerge from this relationship.
Machine Learning for Criminology and Crime Research reviews the roots of the intersection between machine learning, Artificial Intelligence, and research on crime, examines the current state of the art in this area of scholarly inquiry, and discusses future perspectives that may emerge from this relationship.
Gian Maria Campedelli is a Postdoctoral Research Fellow in Computational Sociology and Criminology at the University of Trento, Italy. In 2020, he earned a PhD in Criminology from Catholic University in Milan, Italy. From 2016 to 2019 he worked as a researcher at Transcrime, the Joint Research Center on Transnational Crime of Catholic University, University of Bologna, and University of Perugia. In 2018 he was also a visiting research scholar in the School of Computer Science at Carnegie Mellon University, in Pittsburgh, the United States. His research addresses the development and application of computational methods - especially machine learning and complex networks - to the study of criminal and social phenomena, with a specific focus on organized crime, violence, and terrorism.
Chapter 1: The "Novelty Narrative": An Unorthodox Introduction
Chapter 2: A Collective Journey: A Short Overview on Artificial Intelligence
Chapter 3: Criminology at the Crossroads? Computational Perspectives
Chapter 4: To Reframe and Reform: Increasing the Positive Social Impact of Algorithmic Applications in Research on Crime
Chapter 5: Causal Inference in Criminology and Crime Research and the Promises of Machine Learning
Chapter 6: Concluding Remarks
| Erscheinungsjahr: | 2024 |
|---|---|
| Fachbereich: | Allgemeines |
| Rubrik: | Sozialwissenschaften |
| Medium: | Taschenbuch |
| Seiten: | 176 |
| Inhalt: | Einband - flex.(Paperback) |
| ISBN-13: | 9781032109282 |
| ISBN-10: | 1032109289 |
| Sprache: | Englisch |
| Einband: | Kartoniert / Broschiert |
| Autor: | Campedelli, Gian Maria |
| Hersteller: | Taylor & Francis Ltd |
| Maße: | 230 x 152 x 12 mm |
| Von/Mit: | Gian Maria Campedelli |
| Erscheinungsdatum: | 29.01.2024 |
| Gewicht: | 0,308 kg |
Gian Maria Campedelli is a Postdoctoral Research Fellow in Computational Sociology and Criminology at the University of Trento, Italy. In 2020, he earned a PhD in Criminology from Catholic University in Milan, Italy. From 2016 to 2019 he worked as a researcher at Transcrime, the Joint Research Center on Transnational Crime of Catholic University, University of Bologna, and University of Perugia. In 2018 he was also a visiting research scholar in the School of Computer Science at Carnegie Mellon University, in Pittsburgh, the United States. His research addresses the development and application of computational methods - especially machine learning and complex networks - to the study of criminal and social phenomena, with a specific focus on organized crime, violence, and terrorism.
Chapter 1: The "Novelty Narrative": An Unorthodox Introduction
Chapter 2: A Collective Journey: A Short Overview on Artificial Intelligence
Chapter 3: Criminology at the Crossroads? Computational Perspectives
Chapter 4: To Reframe and Reform: Increasing the Positive Social Impact of Algorithmic Applications in Research on Crime
Chapter 5: Causal Inference in Criminology and Crime Research and the Promises of Machine Learning
Chapter 6: Concluding Remarks
| Erscheinungsjahr: | 2024 |
|---|---|
| Fachbereich: | Allgemeines |
| Rubrik: | Sozialwissenschaften |
| Medium: | Taschenbuch |
| Seiten: | 176 |
| Inhalt: | Einband - flex.(Paperback) |
| ISBN-13: | 9781032109282 |
| ISBN-10: | 1032109289 |
| Sprache: | Englisch |
| Einband: | Kartoniert / Broschiert |
| Autor: | Campedelli, Gian Maria |
| Hersteller: | Taylor & Francis Ltd |
| Maße: | 230 x 152 x 12 mm |
| Von/Mit: | Gian Maria Campedelli |
| Erscheinungsdatum: | 29.01.2024 |
| Gewicht: | 0,308 kg |
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