Daniele P. Radicioni


2024

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Legal Text Reader Profiling: Evidences from Eye Tracking and Surprisal Based Analysis
Calogero J. Scozzaro | Davide Colla | Matteo Delsanto | Antonio Mastropaolo | Enrico Mensa | Luisa Revelli | Daniele P. Radicioni
Proceedings of the Workshop on DeTermIt! Evaluating Text Difficulty in a Multilingual Context @ LREC-COLING 2024

Reading movements and times are a precious cue to follow reader’s strategy, and to track the underlying effort in text processing. To date, many approaches are being devised to simplify texts to overcome difficulties stemming from sentences obscure, ambiguous or deserving clarification. In the legal domain, ensuring the clarity of norms and regulations is of the utmost importance, as the full understanding of such documents lies at the foundation of core social obligations and rights. This task requires determining which utterances and text excerpts are difficult for which (sort of) reader. This investigation is the aim of the present work. We propose a preliminary study based on eye-tracking data of 61 readers, with focus on individuating different reader profiles, and on predicting reading times of our readers.

2020

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LessLex: Linking Multilingual Embeddings to SenSe Representations of LEXical Items
Davide Colla | Enrico Mensa | Daniele P. Radicioni
Computational Linguistics, Volume 46, Issue 2 - June 2020

We present LESSLEX, a novel multilingual lexical resource. Different from the vast majority of existing approaches, we ground our embeddings on a sense inventory made available from the BabelNet semantic network. In this setting, multilingual access is governed by the mapping of terms onto their underlying sense descriptions, such that all vectors co-exist in the same semantic space. As a result, for each term we have thus the “blended” terminological vector along with those describing all senses associated to that term. LESSLEX has been tested on three tasks relevant to lexical semantics: conceptual similarity, contextual similarity, and semantic text similarity. We experimented over the principal data sets for such tasks in their multilingual and crosslingual variants, improving on or closely approaching state-of-the-art results. We conclude by arguing that LESSLEX vectors may be relevant for practical applications and for research on conceptual and lexical access and competence.

2017

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MERALI at SemEval-2017 Task 2 Subtask 1: a Cognitively Inspired approach
Enrico Mensa | Daniele P. Radicioni | Antonio Lieto
Proceedings of the 11th International Workshop on Semantic Evaluation (SemEval-2017)

In this paper we report on the participation of the MERALI system to the SemEval Task 2 Subtask 1. The MERALI system approaches conceptual similarity through a simple, cognitively inspired, heuristics; it builds on a linguistic resource, the TTCS-e, that relies on BabelNet, NASARI and ConceptNet. The linguistic resource in fact contains a novel mixture of common-sense and encyclopedic knowledge. The obtained results point out that there is ample room for improvement, so that they are used to elaborate on present limitations and on future steps.

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TTCS: a Vectorial Resource for Computing Conceptual Similarity
Enrico Mensa | Daniele P. Radicioni | Antonio Lieto
Proceedings of the 1st Workshop on Sense, Concept and Entity Representations and their Applications

In this paper we introduce the TTCS, a linguistic resource that relies on BabelNet, NASARI and ConceptNet, that has now been used to compute the conceptual similarity between concept pairs. The conceptual representation herein provides uniform access to concepts based on BabelNet synset IDs, and consists of a vector-based semantic representation which is compliant with the Conceptual Spaces, a geometric framework for common-sense knowledge representation and reasoning. The TTCS has been evaluated in a preliminary experimentation on a conceptual similarity task.

2011

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An Ontology Based Architecture for Translation
Leonardo Lesmo | Alessandro Mazzei | Daniele P. Radicioni
Proceedings of the Ninth International Conference on Computational Semantics (IWCS 2011)