Towards a Process Mining Approach to Grammar Induction for Digital Libraries

Ferilli, Stefano; Angelastro, Sergio

doi:10.1007/978-3-030-11226-4_23

Cited by 3 publications

(2 citation statements)

References 14 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The resources learned by BLA-BLA may be used as returned by the system, and/or be taken as a basis for further manual refinements. It currently includes several techniques that allow us to learn in a fully automatic way linguistic resources for language identification [26], stopword removal [27], term normalization [28], syntax checking [29] and concept taxonomies [30]. Whenever more texts become available for the language, it is easy to run BLA-BLA again and obtain updated resources.…”

Section: Bla-bla and Connektionmentioning

confidence: 99%

Complement Recognition-Based Formal Concept Analysis for Automatic Extraction of Interpretable Concept Taxonomies from Text

Ferilli

2023

Electronics

View full text Add to dashboard Cite

The increasing scale and pace of the production of digital documents have generated a need for automatic tools to analyze documents and extract underlying concepts and knowledge in order to help humans manage information overload. Specifically, since most information comes in the form of text, natural language processing tools are needed that are able to analyze the sentences and transform them into an internal representation that can be handled by computers to perform inferences and reasoning. In turn, these tools often work based on linguistic resources for the various levels of analysis (morphological, lexical, syntactic and semantic). The resources are language (and sometimes even domain) specific and typically must be manually produced by human experts, increasing their cost and limiting their availability. Especially relevant are concept taxonomies, which allow us to properly interpret the textual content of documents. This paper presents an intelligent module to extract relevant domain knowledge from free text by means of Concept Hierarchy Extraction techniques. In particular, the underlying model is provided using Formal Concept Analysis, while a crucial role is played by an expert system for language analysis that can recognize different types of indirect objects (a component very rich in information) in English.

show abstract

Section: Bla-bla and Connektionmentioning

confidence: 99%

Complement Recognition-Based Formal Concept Analysis for Automatic Extraction of Interpretable Concept Taxonomies from Text

Ferilli

2023

Electronics

View full text Add to dashboard Cite

show abstract

“…Pandolfo [25] described how they built the semantic layer of the Pi lsudski Institute of America digital archive. Ferilli [13] described the work performed to extend the BLA-BLA tool for learning linguistic resources by adding a Grammar Induction feature based on the advanced process mining and management system WoMan. Petrocchi [9] presented a study performed on Google Shopping to showcase how large search engines apply query steering depending on the user's profile.…”

Section: Open Science Publishing and Scientific Workflowsmentioning

confidence: 99%

Digital Libraries

et al. 2020

View full text Add to dashboard Cite

The Italian Research Conference on Digital Libraries (IRCDL) is the annual Italian forum to discuss research topics on Digital Libraries and related technical, practical, and social issues. Along the years, IRCDL touched several aspects underlying the ?Digital Library" domain and promptly adapted to the evolution of the field. Today, the ?Digital Library" field includes theory and practices reflecting the evolution of the role of libraries in the scholarly communication domain, and also embracing scholarly communication and open science. The theme of IRCDL 2019 was ?Digital Libraries: Supporting Open Science". Three main reasons motivated this theme: (i) science is increasingly becoming digital, meaning that research is performed using data services and digital tools; (ii) the results of the research are no longer just traditional scientific publications; (iii) the outcomes of science are increasingly encompassing datasets, software, and experiments. As digital artifacts, such products can be shared and re-used together with the article, thus enabling comprehensive research assessment and various degrees of reproducibility of science. Positive consequences of this shift towards Open Science are: accelerating science, optimizing the cost of research, fraud detection, and fullyfledged scientific reward. Digital Libraries are central in the evolution of research outputs by targeting findability, preservation, interlinking, and re-use of research products and by integrating the components of the scholarly communication process. The conference has been organized in Pisa, and the proceedings are published in the Springer CCIS series Vol. 988 [22]. Pre-print versions, research datasets, and research software relative to the accepted contributions are accessible via Zenodo.org.

show abstract

Digital Libraries: Supporting Open Science

2019

Communications in Computer and Information Science

View full text Add to dashboard Cite

Towards a Process Mining Approach to Grammar Induction for Digital Libraries

Cited by 3 publications

References 14 publications

Complement Recognition-Based Formal Concept Analysis for Automatic Extraction of Interpretable Concept Taxonomies from Text

Complement Recognition-Based Formal Concept Analysis for Automatic Extraction of Interpretable Concept Taxonomies from Text

Digital Libraries

Digital Libraries: Supporting Open Science

Contact Info

Product

Resources

About