Papers by Federico Nanni

6 papers
DeezyMatch: A Flexible Deep Learning Approach to Fuzzy String Matching (2020.emnlp-demos)

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Challenge: DeezyMatch is a free, open-source software library written in Python for fuzzy string matching and candidate ranking.
Approach: They propose to use DeezyMatch to train new classifiers and fine-tune a pretrained model to generate rich vector representations from string inputs.
Outcome: The proposed algorithm can be used to find the best matching candidates in large knowledge bases and query sets.
When Time Makes Sense: A Historically-Aware Approach to Targeted Sense Disambiguation (2021.findings-acl)

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Challenge: a new paper examines whether making NLP models sensitive to time improves their performance . timesensitive Sense Disambiguation is a variation on Word Sense disambiguation . authors present a task to determine whether a token in a text is related to a specific sense .
Approach: They propose a task to determine whether a token in a text is related to a specific sense of a lemma.
Outcome: The proposed model improves when time sensitive, rather than historically-aware, models . the proposed model is a variation on Word Sense Disambiguation (WSD) the proposed method is of more practical relevance to digital history and cultural analysis .
Computational Analysis of Political Texts: Bridging Research Efforts Across Communities (P19-4)

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Challenge: Political scientists have developed and adopted natural language processing (NLP) methods to exploit text as an additional source of data in their analyses.
Approach: This tutorial aims to provide a gentle introduction to methods and tasks related to computational analysis of political texts from both communities.
Outcome: The main goal of this tutorial is to bring the two research communities closer to each other and contribute to faster and more significant developments in this interdisciplinary area.
Identifying Moments of Change from Longitudinal User Text (2022.acl-long)

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Challenge: Identifying changes in individuals’ behaviour and mood via shared content is gaining importance given the global increase in mental health disorders and the limited access to support services.
Approach: They propose a task of identifying moments of change in individuals on the basis of their shared content online.
Outcome: The proposed task is based on 500 manually annotated user timelines and shows that it performs best through context aware sequential modelling.
Creation and evaluation of timelines for longitudinal user posts (2023.eacl-main)

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Challenge: Existing methods for segmenting user posts into timelines improve quality and cost of manual annotation.
Approach: They propose a set of methods for segmenting longitudinal user posts into timelines likely to contain interesting moments of change in a user’s behaviour based on their online posting activity.
Outcome: The proposed framework is able to evaluate two different social media datasets and compares with existing models.
Living Machines: A study of atypical animacy (2020.coling-main)

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Challenge: atypical animacy is the property of being alive, but discrepancies are not uncommon . a typical animate is represented as either animate or inanimate in a text .
Approach: They propose a method for determining whether an entity is represented as animate in a text . they use a nineteenth-century English text to analyze animacy .
Outcome: The proposed method improves on an established animacy dataset and a newly introduced resource.

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