My research interests can be summarized in the four points shown below:
Computational Intelligence. My first research topic consisted in the investigation about the use of Evolutionary Computation and Fuzzy Logic for optimizing the structure of Artificial Neural Network. The goal was to build effective systems for pure classification problems. The designed approaches were mainly applied into the Natural Language Processing field, in particular to the Word Sense Disambiguation (WSD) problem where the aim is to detect the correct sense of an ambiguous word into the different contexts in which such word occurs. This topic has been investigated for the first half of my Ph.D. period.
Information Retrieval. The main topic of my Ph.D., my aim was to evolve the state of the art of IR systems by integrating a multidimensional representation of documents able to increase the effectiveness of both indexing construction and query processing. Together with this, the Computational Intelligence approaches learned during the first part of my Ph.D. were exploited for learning user profiles in order to extend query processing algorithms with a user-based dimension.
Knowledge Management and Semantic Technologies. After moving to Fondazione Bruno Kessler, I have been involved in a strong project-oriented environment. I had to stop working on the research topics studied during my Ph.D. and started to align my competencies with the key-ones of the Data and Knowledge Management group. Thus, I acquired the background of the knowledge management and business process modeling areas for making myself effective on the assigned projects. During the first years, I was mainly involved in project-related activities. In particular, I worked on ontology engineering and process modeling tasks and developed a tools allowing an integrated representation of the produced artifacts. Recent activities concerns the integration of knowledge bases into complex platforms and I restarted to work in the IR field by bringing the acquired competencies and the developed technologies to the goal of evolving what I did during my Ph.D..
Sentiment Analysis and Opinion Mining. In 2013, I started an independent research line: the integration of semantic technologies and fuzzy logic for investigating the semantic sentiment analysis area. In particular, I associate fuzzy representations to the polarity of each concept occurring in a text and to adapt it based on the domain in which each concept occurs. This way, I am able to provide a more flexible representation supporting the design of effective approaches as demonstrated in recent published contributions. Recently, I started to integrate argumentation theory frameworks concerning the analysis of complex scenarios like the ones strongly connected with social sciences, in order to tracking the evolution of opinions and associated sentiment.
Research Metrics (updated July 25th, 2022)
Google Scholar - Citations: 2054 h-Index: 26
Scopus - Citations: 1340 h-Index: 21