2023
Autores
Campos, R; Jorge, A; Jatowt, A; Bhatia, S; Litvak, M;
Publicação
ADVANCES IN INFORMATION RETRIEVAL, ECIR 2023, PT III
Abstract
Over these past five years, significant breakthroughs, led by Transformers and large language models, have been made in understanding natural language text. However, the ability to capture contextual nuances in longer texts is still an elusive goal, let alone the understanding of consistent fine-grained narrative structures in text. These unsolved challenges and the interest in the community are at the basis of the sixth edition of Text2Story workshop to be held in Dublin on April 2nd, 2023 in conjunction with the 45th European Conference on Information Retrieval (ECIR'23). In its sixth edition, we aim to bring to the forefront the challenges involved in understanding the structure of narratives and in incorporating their representation in well-established models, as well as in modern architectures (e.g., transformers) which are now common and form the backbone of almost every IR and NLP application. It is hoped that the workshop will provide a common forum to consolidate the multi-disciplinary efforts and foster discussions to identify the wide-ranging issues related to the narrative extraction and generation task. Text2Story includes sessions devoted to full research papers, work-in-progress, demos and dissemination papers, keynote talks and space for an informal discussion of the methods, of the challenges and of the future of this research area.
2023
Autores
Sousa, MJ; Jamil, G; Walter, CE; Au Yong Oliveira, M; Moreira, F;
Publicação
EXPERT SYSTEMS
Abstract
This study seeks to answer the following research question: "What factors can explain the number of patent filing requests made by residents in Brazil at patent offices in Brazil, the United States, Europe, and triadic patent families?". The methods used in this research are quantitative, using big data from private and public investments in Science and Technology, and about patent deposit numbers in Brazil from 2000 to 2017. A model of linear regression was performed and explains how these investments in Science and Technology influence patent deposit numbers. The results of this research study point towards the importance of universities, up and beyond the traditional training and education aspect of university activity. The importance of public and private innovation investments is also shown to be important. This study shows that the patent registrations in the different regions under analysis are affected by different factors. There is thus no single formula towards the creation of innovation output and governments would do well to continue to invest in higher education while also investing in public research and development activities. Additionally, and not least important, private entities should be continually encouraged to make innovation investments and favourable government policies need to thus exist for this to happen. Finally, the low numbers regarding patent filings in Brazil may be linked to institutional deficiencies in the country. Patent breaches may be difficult to punish, and the judicial system may be slow and untrustworthy, compared to the United States and to Europe-leading to diminished patent registrations in Brazil. A set of implications and recommendations for policy derived from this study and will be strategic for policymakers.
2023
Autores
Jorge, F; Sousa, N; Losada, N; Teixeira, MS; Alén, E; Melo, M; Bessa, M;
Publicação
Journal of Tourism and Development
Abstract
Tourism business models have used several technologies in their development, such as Virtual Reality (VR). Previous studies show that VR allows tourism organizations to promote new types of relationships between tourists and destinations, to enhance the appeal and memorability of tourist experiences and to diversify consumption patterns, which could also be interesting for dealing with sustainability issues, such as seasonal demand of destinations or activities in wine tourism. Thus, we propose a conceptual model to analyze the influence of memorable tourism experiences on wine tourists' future intentions after a VR experience, providing additional details on the research methodology to empirically test the conceptual model. Innovation in business models with VR to promote new relationships with destinations or activities and diversify tourists' consumption patterns could be interesting to address seasonal activities, such as the grape harvest or grape-treading, which are not continuously available for tourist observation/ participation, despite their high appeal. On the other hand, the results could contribute to wine and other kinds of tourism, conditioned by mobility issues such as restrictions on movements or personal interaction, due to health crises or personal constraints, increasing these tourism experiences' accessibility also in times of unavailability. © 2023, Universidade de Aveiro. All rights reserved.
2023
Autores
Machado, F; Duarte, N; Amaral, A; Araújo, M;
Publicação
PROCEEDINGS OF THE 5TH INTERNATIONAL CONFERENCE ON PRODUCTION ECONOMICS AND PROJECT EVALUATION, ICOPEV 2022
Abstract
This paper explores the effects of Industry 5.0 on Sustainable Development. The authors first developed a primer review to introduce the new research agenda of Industry 5.0. Secondly, they performed a state-of-the-art review on the topics of Industry 4.0/Industry 5.0 and Sustainability. The eligible documents have been subjected to a content analysis that identified seven themes. The present research identified a positive relationship between the implementation of Industry 4.0 and sustainable development attainment. This relationship constitutes an opportunity for Industry 5.0 to promote sustainability. Notwithstanding, a series of barriers, drivers and enablers were also identified. Also, this research conclusions are aligned with the explanation presented by the European Commission for the development of the Industry 5.0 concept. However, this will not be enough to shift the paradigm effectively. This paper compiled and analysed the most recent advancements in the new research agenda of Industry4.0/Industry 5.0 dedicated explicitly to sustainability, a topic that requires development in theoretical and empirical research.
2023
Autores
Correia, A; Guimaraes, D; Paredes, H; Fonseca, B; Paulino, D; Trigo, L; Brazdil, P; Schneider, D; Grover, A; Jameel, S;
Publicação
IEEE TRANSACTIONS ON HUMAN-MACHINE SYSTEMS
Abstract
Visualizing and examining the intellectual landscape and evolution of scientific communities to support collaboration is crucial for multiple research purposes. In some cases, measuring similarities and matching patterns between research publication document sets can help to identify people with similar interests for building research collaboration networks and university-industry linkages. The premise of this work is assessing feasibility for resolving ambiguous cases in similarity detection to determine authorship with natural language processing (NLP) techniques so that crowdsourcing is applied only in instances that require human judgment. Using an NLP-crowdsourcing convergence strategy, we can reduce the costs of microtask crowdsourcing while saving time and maintaining disambiguation accuracy over large datasets. This article contributes a next-gen crowd-artificial intelligence framework that used an ensemble of term frequency-inverse document frequency and bidirectional encoder representation from transformers to obtain similarity rankings for pairs of scientific documents. A sequence of content-based similarity tasks was created using a crowd-powered interface for solving disambiguation problems. Our experimental results suggest that an adaptive NLP-crowdsourcing hybrid framework has advantages for inter-researcher similarity detection tasks where fully automatic algorithms provide unsatisfactory results, with the goal of helping researchers discover potential collaborators using data-driven approaches.
2023
Autores
Faria, AS; Soares, T; Goumas, G; Abotzios, A; Cunha, JM; Silva, M;
Publicação
2023 OPEN SOURCE MODELLING AND SIMULATION OF ENERGY SYSTEMS, OSMSES
Abstract
This work aims to present a thorough study of a district heating scenario in a Greek industrial park case. The work is supported by the EMB3Rs open-source platform, allowing to perform a feasibility analysis of the system. In particular, this work explores the market module of this platform to provide a detailed market analysis of energy exchange within the Greek industrial park. The results pinpoint the effectiveness of the platform in simulating different market designs like centralized and decentralized, making clear the potential benefit the sources in the test case may achieve by engaging in a market framework. Different options for market clearing are considered in the study, for instance, including CO2 signals to reach carbon neutrality or community preferences to increase community autonomy. One can conclude that excess heat from existing sources is enough to cover other industries/facilities' heat demand, leading to environmental benefits as well as a fairer financial profits allocation.
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