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Since the early 1990s Massimo Melucci has been carrying out research in Information Retrieval (IR), that is, the automated retrieval of information relevant to users’ needs. In particular, he is interested in modeling, implementating and experimenting advanced methods for indexing, retrieving and ranking documents, recently inspired to physics and engineering disciplines. He has been researching into the correspondence between IR and Quantum Mechanics (QM) both from a theoretical and an experimental perspective, because effective contextual IR systems can be designed within the theoretical framework of QM. Indeed, QM provides a theoretical framework which well describes how contextual factors influence the user’s information need and the retrieval of relevant documents. In the intersection between QM and detection theory, he found that the maximum effectiveness stated by the Probability Ranking Principle for IR can be further improved without additional evidence for estimating the parameters of a probabilistic model.
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Discover Computingno. 1 (2024): 1-24
EXPERT SYSTEMS WITH APPLICATIONS (2024): 122709
Proceedings of the 2021 Conference on Human Information Interaction and Retrieval (2021)
CHIIRpp.349-350, (2021)
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