Ontology-driven Generation of Training Paths in the Legal Domain

Capuano, Nicola; Longhi, Andrea; Salerno, Saverio; Toti, Daniele

doi:10.3991/ijet.v10i7.4609

Cited by 14 publications

(3 citation statements)

References 10 publications

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“…Semantic conflicts are due to the presence of data from multiple sources, that may lead to different interpretations depending on local contexts, causing misunderstandings. This is a problem also felt in other areas including cultural (Capuano, Gaeta, Guarino, Miranda, & Tomasiello, 2016), formative (Capuano, Longhi, Salerno, & Toti, 2015), legal (Hasan, et al, 2021), etc. but particularly relevant in biology and medicine.…”

Section: Related Workmentioning

confidence: 99%

A Semantic Framework Supporting Multilayer Networks Analysis for Rare Diseases

Capuano

Foggia

Greco

et al. 2022

International Journal on Semantic Web and Information Systems

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Understanding the role played by genetic variations in diseases, exploring genomic variants and discovering disease-associated loci are among the most pressing challenges of genomic medicine. A huge and ever-increasing amount of information is available to researchers to address these challenges. Unfortunately, it is stored in fragmented ontologies and databases, which use heterogeneous formats and poorly integrated schemas. To overcome these limitations, we propose a linked data approach, based on the formalism of multilayer networks, able to integrate and harmonize biomedical information from multiple sources into a single dense network covering different aspects on Neuroendocrine Neoplasms (NENs). The proposed integration schema consists of three interconnected layers representing, respectively, information on the disease, on the affected genes, on the related biological processes and molecular functions. An easy-to-use client-server application was also developed to browse and search for information on the model supporting multilayer network analysis.

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Section: Related Workmentioning

confidence: 99%

A Semantic Framework Supporting Multilayer Networks Analysis for Rare Diseases

Capuano

Foggia

Greco

et al. 2022

International Journal on Semantic Web and Information Systems

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“…In more complex systems, additional sanitization techniques can be used [55]. Yet instead of immediately inserting the remaining tokens as features into the computational systems, the query expansion interface strategy builds upon the input profile by injecting insight provided by mediating resources, such as related terms, synonyms, and other expansion opportunities [56]. In other words, these systems utilize mediating resources to computationally expand the query.…”

Section: Query Expansion Interface Strategymentioning

confidence: 99%

Design of Generalized Search Interfaces for Health Informatics

Demelo

Sedig

2021

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In this paper, we investigate ontology-supported interfaces for health informatics search tasks involving large document sets. We begin by providing background on health informatics, machine learning, and ontologies. We review leading research on health informatics search tasks to help formulate high-level design criteria. We use these criteria to examine traditional design strategies for search interfaces. To demonstrate the utility of the criteria, we apply them to the design of ONTology-supported Search Interface (ONTSI), a demonstrative, prototype system. ONTSI allows users to plug-and-play document sets and expert-defined domain ontologies through a generalized search interface. ONTSI’s goal is to help align users’ common vocabulary with the domain-specific vocabulary of the plug-and-play document set. We describe the functioning and utility of ONTSI in health informatics search tasks through a workflow and a scenario. We conclude with a summary of ongoing evaluations, limitations, and future research.

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“…adjective + noun, contiguous upper-case nouns etc. ), according to the process described in [17]; -while the above mentioned language processing is performed, a Wikification process of the original text, based on Wikipedia Miner [18] and originally applied in [19,20] is carried out in order to produce a number of topics from the Wikipedia common-sense knowledge base that are semantically relevant to the given text;…”

Section: Conceptualizationmentioning

confidence: 99%

An Environment for Collective Perception based on Fuzzy and Semantic Approaches

D’Aniello

Loia

Reformat

et al. 2018

Journal of Artificial Intelligence and Soft Computing Research

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This work proposes a software environment implementing a methodology for acquiring and exploiting the collective perception (CP) of Points of Interests (POIs) in a Smart City, which is meant to support decision makers in urban planning and management. This environment relies upon semantic knowledge discovery techniques and fuzzy computational approaches, including natural language processing, sentiment analysis, POI signatures and Fuzzy Cognitive Maps, turning them into a cohesive architectural blend in order to effectively gather the realistic perception of a user community towards given areas and attractions of a Smart City. The environment has been put to the test via a thorough experimentation against a massive user base of an online community with respect to a large metropolitan city (the City of Naples). Such an experimentation yielded consistent results, useful for providing decision makers with a clear awareness of the positive as well as critical aspects of urban areas, and thus helping them shape the measures to be taken for an improved city management and development.

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Ontology-driven Generation of Training Paths in the Legal Domain

Cited by 14 publications

References 10 publications

A Semantic Framework Supporting Multilayer Networks Analysis for Rare Diseases

A Semantic Framework Supporting Multilayer Networks Analysis for Rare Diseases

Design of Generalized Search Interfaces for Health Informatics

An Environment for Collective Perception based on Fuzzy and Semantic Approaches

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