Ernesto William De Luca

Otto-von-Guericke University Magdeburg | OvGU · Department of Technical & Operational Information Systems (ITI)

Natural Language Processing (NLP) is vital for computers to process and respond accurately to human language. However, biases in training data can introduce unfairness, especially in predicting legal judgment. This study focuses on analyzing biases within the Swiss Judgment Prediction Dataset (SJP-Dataset). Our aim is to ensure unbiased factual des...

The real-time availability of information and the intelligence of information systems have changed the way we deal with information. Current research is primarily concerned with the interplay between internal and external memory, i.e., how much and which forms of cognitively demanding processes we handle internally and when we use external storage...

In this paper, we present LUMI, a system that explains document retrieval through span highlighting. LUMI allows users to select a query span and highlights the most relevant part of a retrieved document using transformer-based retrieval, improving transparency in legal and technical analysis.

In this work, we propose a hybrid approach for legal norm retrieval that combines the structural information modeled in knowledge graphs with the textual content of legal documents. Our method utilizes the intricate relationships within the Japanese Civil Code, supplemented by relevant precedents, references, commentary, and mentions in legal textb...

The concept of human-centeredness exists in the fields of software ergonomics and artificial intelligence. In this work, we propose how key principles from both disciplines can be applied together in a unified software design process. While the research community for legal artificial intelligence is well-aware of common requirements, such as explai...

This paper presents TENJI, a system for exploring a knowledge graph based on legal textbooks, norms, and court decisions. TENJI reveals relationships between legal documents by enabling traversal of citation graphs and references extracted from textbooks. Since textbooks provide contextual legal knowledge that is not always explicit in the norms, T...

Diffusion-based recommender systems have recently proven to outperform traditional generative recommendation approaches, such as variational autoencoders and generative adversarial networks. Nevertheless, the machine learning literature has raised several concerns regarding the possibility that diffusion models, while learning the distribution of d...

User modeling is a key topic in many applications, mainly social networks and information retrieval systems. To assess the effectiveness of a user modeling approach, its capability to classify personal characteristics (e.g., the gender, age, or consumption grade of the users) is evaluated. Due to the fact that some of the attributes to predict are...

In this study, we propose a visualization technique to explore and visualize concept hierarchies generated from a textbook in the legal domain. Through a human-centered design process, we developed a tool that allows users to effectively navigate through and explore complex hierarchical concepts in three kinds of traversal techniques: top-down, mid...

Purpose This article aims to explore how the mapping strategies between user requirements expressed by the humanities researchers lead to a better customization of user-driven digital humanities tools and to the creation of innovative functionalities, which can directly affect the way of doing research in a digital context. Design/methodology/appr...

In this work, we imitate the process of a legal expert studying the situational application of statutes, in order to infer relevance and entailment relationships between a query statement and a statute. While using transformer-based architectures, we extract additional statute information from textbooks and incorporate this knowledge into the origi...

The daily use of social networks and the resulting dissemination of disinformation over those media have greatly contributed to the rise of the fake news phenomenon as a global problem. Several manual and automatic approaches are currently in place to try to tackle and defuse this issue, which is becoming nearly uncontrollable. In this paper, we pr...

Digital Humanities (DH) provide a broad spectrum of functionalities and tools that enable the enrichment of both quantitative and qualitative research methods in the humanities. It has been widely recognized that DH can help in curating and analysing large amounts of data. However, digital tools can also support research processes in the humanities...

The availability of videos has grown rapidly in recent years. Finding and browsing relevant information to be automatically extracted from videos is not an easy task, but today it is an indispensable feature due to the immense number of digital products available. In this paper, we present a system which provides a process to automatically extract...

Despite the existing skepticism about the use of automatic systems in contexts where human knowledge and experience are considered indispensable (e.g., the granting of a mortgage, the prediction of stock prices, or the detection of cancers), our work aims to show how the use of explainability and fairness techniques can lead to the growth of a doma...

Textual entailment classification is one of the hardest tasks for the Natural Language Processing community. In particular, working on entailment with legal statutes comes with an increased difficulty, for example in terms of different abstraction levels, terminology and required domain knowledge to solve this task. In course of the COLIEE competit...

Edumeres Toolbox is a tool that helps researchers in the quantitative and qualitative analysis of large textbook collections. It belongs to the family of CAQDAS products: tools that allow text research to be simplified through automated text analysis. This paper analyses how the product is structured, its functionality and its architecture. It then...

This paper presents a study of a strategy for automated cataloging within an OPAC or for online bibliographic catalogs generally. The aim of the analysis is to offer a set of results, while searching in library catalogs, that goes further than the expected one-to-one term correspondence. The goal is to understand how ontological structures can affe...

In the age of digital information, where the internet and social networks, as well as personalised systems, have become an integral part of everyone’s life, it is often challenging to be aware of the amount of data produced daily and, unfortunately, of the potential risks caused by the indiscriminate sharing of personal data. Recently, attention to...

In recent years the explosion in high-performance computing systems and high-capacity storage has led to an exponential increase in the amount of information, generating the phenomenon of big data and the development of automatic processing models like machine learning analysis. In this paper a machine learning time series analysis was experimental...

In an ever more digitized world where information and data are increasingly dematerialized, the question of how to certify intellectual property and define when a document has been created or modified without the presence of any third-party guarantor inevitably arises. This document proposes a decentralized method that, by exploiting blockchain tec...

There are several areas in which organisations can adopt technologies that will support decision-making: artificial intelligence is one of the most innovative technologies that is widely used to assist organisations in business strategies, organisational aspects and people management. In recent years, attention has increasingly been paid to human r...

Historically grown research projects, run by researchers with limited understanding of data sustainability, data reusability and standards, often lead to data silos. While the data are very valuable it can not be used by any service except the tool it was prepared for. Over the years, the number of such data graveyards will increase because new pro...

As a non-university research institution, the Georg Eckert Institute for International Textbook Research (GEI) conducts and facilitates fundamental research into textbooks and educational media primarily informed by history and cultural studies. For this purpose, the GEI provides research infrastructures such as its renowned research library and va...

The investigation of sanctioned knowledge for the formation of the young generation is a subject of textbook research. Additionally, textbooks are gaining importance for historical research in other disciplines, in the search for “popular knowledge”, as they reflect worldviews, thought flows and desired knowledge. Therefore, it is important to have...

The Georg Eckert Institute conducts applied, interdisciplinary research into textbooks and educational media, owning an important digitalized document corpus. Current Digital Libraries technologies don’t allow its researchers to fully exploit the potential offered by Natural Language Processing technologies, thus a new platform, based on open sourc...

This paper presents the transdisciplinary work on digital tools in the field of textual analysis. The availability of digitized or digital born textual sources provides opportunities for automatized analyses and new forms of support for researchers by information technology. However, this can only be successful under the condition that humanists an...

In recent years, many data visualization tools have appeared on the market that can potentially guarantee citizens and users of the Public Administration (PA) the ability to create dashboards and data stories with just a few clicks, using open and unopened data from the PA. The Data Analytics Framework (DAF), a project of the Italian government lau...

In our society we are continually invested by a stream of information (opinions, preferences, comments, etc.). This shows how Twitter users react to news or events that they attend or take part in real time and with interest. In this context it becomes essential to have the appropriate tools in order to be able to analyze and extract data and infor...

This paper explains the connection and mapping of knowledge representations between RDF and CMDI. Therefore, the challenge is to create a bridge between Linked Open Data (LOD) and the Component MetaData Infrastructure (CMDI) to ensure that the limits of the two paradigms are compensated and strengthened to create a new hybrid approach. While on the...

The principles of open data and the five-star model allow companies to develop low-cost services and Public Administrations (PA) to improve efficiency. However, the process of implementing open data models and principles is not easy unless it is supported by an appropriate technology platform. Today there is a huge number of technological platforms...

This paper analyses the establishment of a common infrastructure standard covering metadata, content, and inferred knowledge to allow collaborative work between researchers in the humanities. Interoperability between heterogeneous resources and services is the key for a properly functioning infrastructure. In this paper, we present a digital infras...

This book constitutes the thoroughly refereed proceedings of the 13th International Conference on Metadata and Semantic Research, MTSR 2019, held in Rome, Italy, in October 2019. The 27 full and 15 short papers presented were carefully reviewed and selected from 96 submissions. The papers are organized in the following tracks: metadata and semantic...

The purpose of this article is to introduce the Lean Six Sigma (LSS) DMAIC (Define, Measure, Analyze, Improve, Control) roadmap for quality assurance in biomedical ontologies, by applying Lean Six Sigma principles to Ontology Engineering and Collaboration Engineering. Collaboration lies at the human core of social processes and interactions, where...

In this paper, we give an overview about the current research in Big Data and Digital Curation with a focus on Lean Six Sigma and discuss how this methodology can help the Digital Curation lifecycle. For instance, the application of the Lean Six Sigma methodology is presented and discussed with a special focus on the selection, preservation, mainte...

Knowledge Management can be essential for handling disaster information, creating knowledge bases that can cover very complex events and can vary in size and type. The challenge is to establish mechanisms for the correlation of data coming from various sources to support the Humanitarian Assistance and Disaster Relief (HADR). We propose a method fo...

This editorial describes the workshop outline and overview of presented papers at the 15th European Networked Knowledge Organization Systems Workshop (NKOS 2016) in Hannover, Germany.

Expert finding and the identification of similar professionals are important tasks for many services provided by companies and institutions. Most of research works focus on a limited set of users, characterized by the same kind of main activities , e.g., researchers, or exploit external knowledge, such as predefined ontologies. An heterogeneous env...

Expert finding and the identification of similar professionals are important tasks for many services provided by companies and institutions. Nowadays, the rapid growth of web services and social and professional networks, allowed different kind of users to share personal data and increased the amount of information available. Most of research works...

Context-aware information is widely available in various ways and is becoming more and more important for enhancing retrieval performance and recommendation results. The current main issue to cope with is not only recommending or retrieving the most relevant items and content, but defining them ad hoc. Other relevant issues include personalizing an...

Sehr viele Informationen sind bereits im Web verfügbar oder können aus isolierten strukturierten Datenspeichern wie Informationssystemen und sozialen Netzwerken gewonnen werden. Datenintegration durch Nachbearbeitung oder durch Suchmechanismen (z. B. D2R) ist deshalb wichtig, um Informationen allgemein verwendbar zu machen. Semantische Technologien...

A lot of information that is already available on the Web, or retrieved from local information systems and social networks is structured in data silos that are not semantically related. Semantic technologies make it emerge that the use of typed links that directly express their relations are an advantage for every application that can reuse the inc...

The SPIM workshop focuses especially on people that are working on the social or semantic Web, machine learning, user modeling, recommender systems, information retrieval, semantic interaction, or their combination. The goal is to bring together researchers and practitioners to initiating discussions on the different requirements and challenges com...

The challenge and workshop on Context-Aware Movie Recommendation (CAMRa2010) were conducted jointly in 2010 with the Recommender Systems conference. The challenge focused on three context-aware recommendation scenarios: time-based, mood-based, and social recommendation. The participants were provided with anonymized datasets from two real-world onl...

Recommender Systems refer to those applications that offer contents or items to the users, based on their previous activity. These systems are broadly used in several fields and applications, being common that an user interact with several recommender systems during his daily activities. However, most of these systems are black boxes which users re...

A lot of information that is already available on the Web, or retrieved from local information systems and social networks, is structured in data silos that are not semantically related. Semantic technologies make it apparent that the use of typed links that directly express their relations are an advantage for every application that can reuse the...

CARS 2012 builds upon the success of the three previous editions held in conjunction with the 3rd to 5th ACM Conferences on Recommender Systems from 2009 to 2011. The 1st CARS Workshop was held in New York, NY, USA, whereas Barcelona, Spain, was home of the 2nd CARS Workshop in 2010. In 2011, the 3rd CARS workshop was held in Chicago, IL, USA.

Collaborative Filtering Recommender Systems come in a wide variety of variants. In this paper we present a system for visualizing and comparing recommendations provided by different collaborative recommendation algorithms. The system utilizes a set of context-aware, hybrid, and other collaborative filtering solutions in order to generate various re...

Context-aware information is widely available in various ways and is becoming more and more important for enhancing retrieval performance and recommendation results. The current main issue to cope with is not only recommending or retrieving the most relevant items and content, but defining them ad hoc. Other relevant issues include personalizing an...

This chapter gives a comprehensive overview of ongoing research about semantic approaches for Collaboration Engineering. We will present a new ontology-based approach, where each concept of the ontology corresponds to a specific collaboration step or a resource, to collect, manages and share collaboration knowledge. We discuss the utility of the pr...

In this chapter, the author presents his approach to aggregating and maintaining Multilingual Linked Data. He describes Lexical Resources and Lexical Linked Data, presenting a hybridization that ports the largest lexical resource EuroWordNet to the Linked Open Data cloud, interlinking it with other lexical resources. Furthermore, he shows the LexiR...

Tweets contain mentions of numerous entities, persons and events, and often additional information, like an opinion, that can be viewed as an annotation of that entity. However, this information is currently being accumulated only by specific applications without being made available in a generic format. We discuss a natural language processing app...

Movie recommender systems attempt to find movies which are of interest for their users. However, as new movies are added, and new users join movie recommendation services, the problem of recommending suitable items becomes increasingly harder. In this paper, we present a simple way of using a priori movie data in order to improve the accuracy of co...

This paper provides an overview of CAMRa2011, the second edition of the Challenge on Context-Aware Movie Recommendation. The challenge attracted a large number of participants to work on the challenge tracks, which this time focused on group related recommendation aspects.

The 2011 Challenge on Context-Aware Movie Recommendation (CAMRa2011) was held in conjunction with the Fifth ACM Conference on Recommender Systems (RecSys2011). The challenge focused on group-based recommendation for households, as well as identification of household members who had rated specific movies. The participants were provided with anonymiz...

Nowadays computer scientists are faced with fast growing and permanently evolving data, which are represented as observations made sequentially in time. A common problem in the data mining community is the recognition of recurring patterns within temporal databases or streaming data. This dissertation proposal aims at developing and investigating e...