Pablo García Bringas

dblp:35/6923 · DBLP profile ↗
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10ranked-venue papers in the field
1as first author
2since 2021 · last 2024
0000-0003-3594-9534ORCID · verified

Domains — venue-derived; a paper can count in several

Database Systems & Data Management · 5 (1 first)Big Data, Cloud & Distributed Data Systems · 2Knowledge Engineering, Semantic Web & Information Systems · 2Other / Interdisciplinary · 1
YearPublicationVenuePosition
2024 Creating, Using and Assessing a Generative-AI-Based Human-Chatbot-Dialogue Dataset with User-Interaction Learning Capabilities
abstract
The study illustrates a first step towards an ongoing work aimed at developing a dataset of dialogues potentially useful for customer service conversation management between humans and AI chatbots. The approach exploits ChatGPT 3.5 to generate dialogues. One of the requirements is that the dialogue is characterized by a specific language proficiency level of the user; the other one is that the user expresses a specific emotion during the interaction. The generated dialogues were then evaluated for overall quality. The complexity of the language used by both humans and AI agents, has been evaluated by using standard complexity measurements. Furthermore, the attitudes and interaction patterns exhibited by the chatbot at each turn have been stored for further detection of common conversation patterns in specific emotional contexts. The methodology could improve human-AI dialogue effectiveness and serve as a basis for systems that can learn from user interactions.
Alfredo Cuzzocrea, Giovanni Pilato, Pablo García Bringas
IEEE Big Data3
2024 A Systematic Literature Review of Decentralized Applications in Web3: Identifying Challenges and Opportunities for Blockchain Developers
abstract
The Internet has opened the floor to stakeholders by redefining the way of organizing, communicating, and collaborating that was initiated by the Web’s development. The advancement of the World Wide Web is an outright phenomenon and significant and we witnessed the evolution of the Web. As decentralized technologies continue to gain traction, Web3, or the decentralized internet, has emerged as a promising approach to enable a more secure, transparent, and privacy-preserved digital landscape. In this paper, we thoroughly conduct a systematic study to explore the challenges and opportunities encountered by blockchain developers in the context of decentralized applications (dApps) in Web3. We analyze a set of peer-reviewed research articles, whitepapers, and technical reports and present an in-depth understanding of the current state of Web3 development and its implications. Our finding indicates the opportunities that Web3 can facilitate, such as expanded use cases, enhanced security and privacy, decentralized infrastructure, and the potential for enabling inclusive development resources for blockchain developers. Additionally, we highlight various challenges that blockchain developers deal with including scalability, security, privacy, interoperability, and the need for standardized tools and frameworks along with various challenges in the software development lifecycle (SDLC). While there are significant challenges to overcome, the potential benefits of Web3 are substantial and could lead to a more inclusive, secure, and transparent digital ecosystem. Furthermore, we emphasize the importance of continued research, collaboration, and innovation among stakeholders to address the identified challenges and capitalize on Web3’s opportunities.
Md. Jobair Hossain Faruk, Pratusha Raya, Md Kamrul Siam, Jerry Q. Cheng, Hossain Shahriar, Alfredo Cuzzocrea, Pablo García Bringas
IEEE Big Data7
2019 Can BlockChain Technology Provide Information Systems with Trusted Database? The Case of HyperLedger Fabric
Pablo García Bringas, Iker Pastor-López, Giuseppe Psaila
FQAS1
2014 Study on the effectiveness of anomaly detection for spam filtering
Carlos Laorden, Xabier Ugarte-Pedrero, Igor Santos, Borja Sanz 0001, Javier Nieves, Pablo García Bringas
Inf. Sci.6
2013 Opcode sequences as representation of executables for data-mining-based unknown malware detection
Igor Santos, Felix Brezo, Xabier Ugarte-Pedrero, Pablo García Bringas
Inf. Sci.4
2012 Supervised classification of packets coming from a HTTP botnet
abstract
The posibilities that the management of a vast amount of computers and/or networks offer, is attracting an increasing number of malware writers. In this document, the authors propose a methodology thought to detect malicious botnet traffic, based on the analysis of the packets flow that circulate in the network. This objective is achieved by means of the parametrization of the static characteristics of packets, which are lately analysed using supervised machine learning techniques focused on traffic labelling so as to face proactively to the huge volume of information nowadays filters work with.
Felix Brezo, José Gaviria de la Puerta, Xabier Ugarte-Pedrero, Igor Santos, Pablo García Bringas, David Barroso
CLEI5
2012 Combination of Machine-Learning Algorithms for Fault Prediction in High-Precision Foundries
Javier Nieves, Igor Santos, Pablo García Bringas
DEXA (2)3
2011 Anomaly Detection for the Prediction of Ultimate Tensile Strength in Iron Casting Production
Igor Santos, Javier Nieves, Xabier Ugarte-Pedrero, Pablo García Bringas
DEXA (2)4
2010 Automatic Morphological Categorisation of Carbon Black Nano-aggregates
Juan López-de-Uralde, Iraide Ruiz, Igor Santos, Agustín Zubillaga, Pablo García Bringas, Ana Okariz, Teresa Guraya
DEXA (2)5
2010 Enhanced Foundry Production Control
Javier Nieves, Igor Santos, Yoseba K. Penya, Felix Brezo, Pablo García Bringas
DEXA (1)5