TY - JOUR T1 - Survey on using constraints in data mining JF - Data Mining and Knowledge Discovery Y1 - 2017 A1 - Valerio Grossi A1 - Andrea Romei A1 - Franco Turini AB - This paper provides an overview of the current state-of-the-art on using constraints in knowledge discovery and data mining. The use of constraints in a data mining task requires specific definition and satisfaction tools during knowledge extraction. This survey proposes three groups of studies based on classification, clustering and pattern mining, whether the constraints are on the data, the models or the measures, respectively. We consider the distinctions between hard and soft constraint satisfaction, and between the knowledge extraction phases where constraints are considered. In addition to discussing how constraints can be used in data mining, we show how constraint-based languages can be used throughout the data mining process. VL - 31 ER - TY - CONF T1 - The layered structure of company share networks T2 - Data Science and Advanced Analytics (DSAA), 2015. 36678 2015. IEEE International Conference on Y1 - 2015 A1 - Andrea Romei A1 - Salvatore Ruggieri A1 - Franco Turini AB - We present a framework for the analysis of corporate governance problems using network science and graph algorithms on ownership networks. In such networks, nodes model companies/shareholders and edges model shares owned. Inspired by the widespread pyramidal organization of corporate groups of companies, we model ownership networks as layered graphs, and exploit the layered structure to design feasible and efficient solutions to three key problems of corporate governance. The first one is the long-standing problem of computing direct and indirect ownership (integrated ownership problem). The other two problems are introduced here: computing direct and indirect dividends (dividend problem), and computing the group of companies controlled by a parent shareholder (corporate group problem). We conduct an extensive empirical analysis of the Italian ownership network, which, with its 3.9M nodes, is 30× the largest network studied so far. JF - Data Science and Advanced Analytics (DSAA), 2015. 36678 2015. IEEE International Conference on PB - IEEE ER - TY - JOUR T1 - A multidisciplinary survey on discrimination analysis JF - The Knowledge Engineering Review Y1 - 2014 A1 - Andrea Romei A1 - Salvatore Ruggieri AB - The collection and analysis of observational and experimental data represent the main tools for assessing the presence, the extent, the nature, and the trend of discrimination phenomena. Data analysis techniques have been proposed in the last 50 years in the economic, legal, statistical, and, recently, in the data mining literature. This is not surprising, since discrimination analysis is a multidisciplinary problem, involving sociological causes, legal argumentations, economic models, statistical techniques, and computational issues. The objective of this survey is to provide a guidance and a glue for researchers and anti-discrimination data analysts on concepts, problems, application areas, datasets, methods, and approaches from a multidisciplinary perspective. We organize the approaches according to their method of data collection as observational, quasi-experimental, and experimental studies. A fourth line of recently blooming research on knowledge discovery based methods is also covered. Observational methods are further categorized on the basis of their application context: labor economics, social profiling, consumer markets, and others. VL - 29 ER - TY - JOUR T1 - Discrimination discovery in scientific project evaluation: A case study JF - Expert Systems with Applications Y1 - 2013 A1 - Andrea Romei A1 - Salvatore Ruggieri A1 - Franco Turini VL - 40 ER - TY - CONF T1 - A Case Study in Sequential Pattern Mining for IT-Operational Risk T2 - ECML/PKDD (1) Y1 - 2008 A1 - Valerio Grossi A1 - Andrea Romei A1 - Salvatore Ruggieri JF - ECML/PKDD (1) ER - TY - CHAP T1 - Discovering Strategic Behaviour in Multi- Agent Scenarios by Ontology-Driven Mining T2 - Advances in Robotics, Automation and Control Y1 - 2008 A1 - Davide Bacciu A1 - Andrea Bellandi A1 - Barbara Furletti A1 - Valerio Grossi A1 - Andrea Romei JF - Advances in Robotics, Automation and Control SN - 978-953-7619-16-9 UR - http://www.intechopen.com/books/advances_in_robotics_automation_and_control/discovering_strategic_behaviors_in_multi-agent_scenarios_by_ontology-driven_mining ER - TY - CONF T1 - Ontological Support for Association Rule Mining T2 - IASTED International Conference on Artificial Intelligence and Applications (AIA) Y1 - 2008 A1 - Barbara Furletti A1 - Andrea Bellandi A1 - Valerio Grossi A1 - Andrea Romei JF - IASTED International Conference on Artificial Intelligence and Applications (AIA) CY - Innsbruck, Austria ER - TY - CONF T1 - Ontology-Driven Association Rule Extraction: A Case Study T2 - International Workshop on Contexts and Ontologies: Representation and Reasoning Y1 - 2007 A1 - Barbara Furletti A1 - Andrea Bellandi A1 - Valerio Grossi A1 - Andrea Romei JF - International Workshop on Contexts and Ontologies: Representation and Reasoning CY - Roskilde, Denmark UR - http://ceur-ws.org/Vol-298/paper1.pdf ER - TY - CONF T1 - PUSHING CONSTRAINTS IN ASSOCIATION RULE MINING: AN ONTOLOGY-BASED APPROACH T2 - IADIS International Conference WWW/Internet 2007 Y1 - 2007 A1 - Barbara Furletti A1 - Andrea Bellandi A1 - Andrea Romei A1 - Valerio Grossi JF - IADIS International Conference WWW/Internet 2007 SN - 978-972-8924-44-7 UR - http://www.iadisportal.org/digital-library/mdownload/pushing-constraints-in-association-rule-mining-an-ontology-based-approach ER -