SEPIR: a semantic and personalised information retrieval tool for the public administration based on distributional semantics

This paper introduces a semantic and personalised information retrieval (SEPIR) tool for the public administration of Apulia Region. SEPIR, through semantic search and visualisation tools, enables the analysis of a large amount of unstructured data and the intelligent access to information. At the core of these functionalities is an NLP pipeline responsible for the WordSpace building and the key-phrase extraction. The WordSpace is the key component of the semantic search and personalisation algorithm. Moreover, key-phrases enrich the document representation of the retrieval system and are on the basis of the bubble charts, which provide a quick overview of the main concepts involved in a document collection. We show some of the key features of SEPIR in a use case where the personalisation technique re-ranks the set of relevant documents on the basis of the user's past queries and the visualisation tools provide the users with useful information about the analysed collection.