[u' @incollection{bilbao_jayo_alisis_2022, title = {An\xe1lisis autom\xe1tico del discurso en redes sociales mediante inteligencia artificial}, isbn = {978-84-254-4959-8}, booktitle = {Transformaci\xf3n y {Espiritualidad}}, publisher = {Herder}, author = {Bilbao Jayo, Aritz and Almeida, Aitor}, month = jun, year = {2022}, keywords = {CNN, NLP, artificial intelligence, deep learning, embeddings, machine learning, natural language processing, political discourse, politics, social networks, transformers}, pages = {283--304}, } ']

[u' @inproceedings{almeida_ontology_2022, address = {Split}, title = {An {Ontology} for {Quality} of {Life} {Modeling} in {Head} and {Neck} {Cancer}}, isbn = {978-953-290-115-3}, abstract = {As survivorship chances for cancer improve, the necessity to properly manage the quality of life post-treatment increases. Head and Neck Cancer is one of the most prevalent ones (being the seventh most common cancer in the world). In this paper we introduce the BD4QoL Ontology, which provides a comprehensive and integrated data model for H\\&N cancer survivors. The presented ontology models several relevant areas of the knowledge domain: the patients clinical and demographic data, the questionnaires commonly used to ascertain their QoL and the related behavioral and emotional traits that can be used to infer the QoL.}, booktitle = {Proceedings of the 7th {International} {Conference} on {Smart} and {Sustainable} {Technologies} ({Splitech} 2022)}, publisher = {FESB, University of Split}, author = {Almeida, Aitor and Bilbao Jayo, Aritz and Hernandez, Liss and Lopez-Perez, Laura and Est\xe9vez-Priego, Estefania and Fico, Giuseppe and Taylor, Katherine and Singer, Susanne and Mercalli, Franco and Filippidou, Despina Elisabeth and Martinelli, Elena and Cavalieri, Stefano and Licitra, Lisa}, month = apr, year = {2022}, keywords = {AI for health, QoL, artificial intelligence, bd4qol, behavior modelling, cancer, head and neck cancer, ontologies, quality of life, wos}, } ']

[u' @inproceedings{cavalieri_bd4qol_2022, address = {Paris, France}, title = {{BD4QoL}: {A} multicenter randomized trial for monitoring quality of life ({QoL}) by intelligent tools in head and neck cancer ({HNC}) survivors after curative treatment}, url = {https://www.esmo.org/meetings/esmo-congress-2022}, language = {English}, booktitle = {Proceedings of the {ESMO} 2022 {Congress}}, author = {Cavalieri, Stefano and Vener, Claudia and LeBlanc, Marissa and L\xf3pez-Perez, Laura and Fico, Giuseppe and Resteghini, Carlo and Monzani, Dario and Marton, Giulia and Moreira-Soares, Mauricio and Despina Elizabeth, Filippidou and Almeida, Aitor and Bilbao Jayo, Aritz and Mehanna, Hisham and Singer, Susanne and Thomas, Steve and Lacerenza, L. and Manfuso, Alonso and Mercalli, Franco and Martinelli, Elena and Licitra, Lisa}, month = sep, year = {2022}, keywords = {AI for health, Artificial Intelligence, BD4QoL, Data analysis, QoL, Quality of life, cancer, clinical trial, head and neck cancer, wos}, } ']

[u' @article{almeida_comparative_2022, title = {A {Comparative} {Analysis} of {Human} {Behavior} {Prediction} {Approaches} in {Intelligent} {Environments}}, volume = {22}, issn = {1424-8220}, url = {https://www.mdpi.com/1424-8220/22/3/701}, doi = {https://doi.org/10.3390/s22030701}, abstract = {Behavior modeling has multiple applications in the intelligent environment domain. It has been used in different tasks, such as the stratification of different pathologies, prediction of the user actions and activities, or modeling the energy usage. Specifically, behavior prediction can be used to forecast the future evolution of the users and to identify those behaviors that deviate from the expected conduct. In this paper, we propose the use of embeddings to represent the user actions, and study and compare several behavior prediction approaches. We test multiple model (LSTM, CNNs, GCNs, and transformers) architectures to ascertain the best approach to using embeddings for behavior modeling and also evaluate multiple embedding retrofitting approaches. To do so, we use the Kasteren dataset for intelligent environments, which is one of the most widely used datasets in the areas of activity recognition and behavior modeling.}, language = {English}, number = {3}, journal = {Sensors}, author = {Almeida, Aitor and Bermejo, Unai and Bilbao Jayo, Aritz and Azkune, Gorka and Aguilera, Unai and Emaldi, Mikel and Dornaika, Fadi and Arganda-Carreras, Ignacio}, month = jan, year = {2022}, keywords = {AI for health, CNN, JCR3.576, LSTM, Q1, activity recognition, artificial intelligence, attention, behavior modelling, behaviour prediction, convolutional networks, embeddings, futuraal, geometric deep learning, graph neural networks, knowledge graphs, machine learning, recurrent neural networks, transformers}, pages = {701}, } ']

[u' @article{bilbao_jayo_location_2022, title = {Location {Based} {Indoor} and {Outdoor} {Lightweight} {Activity} {Recognition} {System}}, volume = {11}, copyright = {http://creativecommons.org/licenses/by/3.0/}, issn = {2079-9292}, url = {https://www.mdpi.com/2079-9292/11/3/360}, doi = {10.3390/electronics11030360}, abstract = {In intelligent environments one of the most relevant information that can be gathered about users is their location. Their position can be easily captured without the need for a large infrastructure through devices such as smartphones or smartwatches that we easily carry around in our daily life, providing new opportunities and services in the field of pervasive computing and sensing. Location data can be very useful to infer additional information in some cases such as elderly or sick care, where inferring additional information such as the activities or types of activities they perform can provide daily indicators about their behavior and habits. To do so, we present a system able to infer user activities in indoor and outdoor environments using Global Positioning System (GPS) data together with open data sources such as OpenStreetMaps (OSM) to analyse the user\\’s daily activities, requiring a minimal infrastructure.}, language = {en}, number = {3}, urldate = {2022-01-25}, journal = {Electronics}, author = {Bilbao Jayo, Aritz and Cantero, Xabier and Almeida, Aitor and Fasano, Luca and Montanaro, Teodoro and Sergi, Ilaria and Patrono, Luigi}, month = jan, year = {2022}, keywords = {AI for health, IoT, JCR2.397, Q2, activity recognition, ambient assisted living, artificial intelligence, bd4qol, behavior modelling, futuraal, indoor positioning, internet of things, performance, smartphone, smartwatch, wearable device}, pages = {360}, } ']

[u' @article{cavalieri_708tip_2022, title = {{708TiP} {BD4QoL}: {A} multicenter randomized trial for monitoring quality of life ({QoL}) by intelligent tools in head and neck cancer ({HNC}) survivors after curative treatment}, volume = {33}, issn = {09237534}, shorttitle = {{708TiP} {BD4QoL}}, url = {https://linkinghub.elsevier.com/retrieve/pii/S0923753422026837}, doi = {10.1016/j.annonc.2022.07.832}, abstract = {HNC survivors suffer from high physical, psychological and socioeconomic burdens. Achieving cancer-free survival with an optimal QoL is the primary goal for HNC patients (pts) management. Therefore, maintaining lifelong surveillance is critical. This can be carried out by advanced analysis of environmental, emotional and behavioral data unobtrusively collected from mobile devices. The aim of this clinical trial is to reduce, with specific non-invasive tools (i.e., their mobile devices), the proportion of HNC survivors experiencing a clinically meaningful reduction in QoL during post-treatment follow-up.}, language = {en}, number = {7}, urldate = {2022-10-20}, journal = {Annals of Oncology}, author = {Cavalieri, Stefano and Vener, Claudia and LeBlanc, Marissa and Lopez Perez, Laura and Fico, Giuseppe and Resteghini, Carlo and Monzani, Dario and Marton, Giulia and Moreira-Soares, Mauricio and Filippidou, Filippidou Despina and Almeida, Aitor and Bilbao Jayo, Aritz and Mehanna, Hisham and Singer, Susanne and Thomas, Steve and Lacerenza, L. and Manfuso, Alonso and Mercalli, Franco and Martinelli, Elena and Licitra, Lisa}, month = jan, year = {2022}, keywords = {AI for health, BD4QoL, JCR51.769, Q1, QoL, behavior modelling, cancer, clinical trial, head and neck cancer, quality of life}, pages = {S866}, } ']

[u' @article{sanchez-corcuera_analysing_2021, title = {Analysing centralities for organisational role inference in online social networks}, volume = {99}, issn = {09521976}, url = {https://linkinghub.elsevier.com/retrieve/pii/S0952197620303663}, doi = {10.1016/j.engappai.2020.104129}, abstract = {The intensive use of Online Social Networks (OSN) nowadays has made users expose more information without realising it. Malicious users or marketing agencies are now able to infer information that is not published on OSNs by using data from targets friends to use for their benefit. In this paper, the authors present a generalisable method capable of deducing the roles of employees of an organisation using their Twitter relationships and the features of the graph from their organisation. The authors also conduct an extensive analysis of the node centralities to study their roles in the inference of the different classes proposed. Derived from the experiments and the ablation study conducted to the centralities, the authors conclude that the latent features of the graph along with the directed relationships perform better than previously proposed methods when classifying the role of the employees of an organisation. Additionally, to evaluate the method, the authors also contribute with a new dataset consisting of three directed graphs (one for each organisation) representing the relationships between the employees obtained from Twitter.}, language = {en}, urldate = {2021-01-04}, journal = {Engineering Applications of Artificial Intelligence}, author = {S\xe1nchez-Corcuera, Rub\xe9n and Bilbao-Jayo, Aritz and Zulaika, Unai and Almeida, Aitor}, month = mar, year = {2021}, keywords = {Adversarial information retrieval, Artificial Intelligence, Graph centralities, IF4.201, Information inference, Online social networks, Q1, machine learning, social network analysis, social networks}, pages = {104129}, } ']

[u' @article{bilbao_jayo_behavior_2021, title = {Behavior {Modeling} for a {Beacon}-{Based} {Indoor} {Location} {System}}, volume = {21}, issn = {1424-8220}, url = {https://www.mdpi.com/1424-8220/21/14/4839}, doi = {10.3390/s21144839}, abstract = {In this work we performed a comparison between two different approaches to track a person in indoor environments using a locating system based on BLE technology with a smartphone and a smartwatch as monitoring devices. To do so, we provide the system architecture we designed and describe how the different elements of the proposed system interact with each other. Moreover, we have evaluated the system\u2019s performance by computing the mean percentage error in the detection of the indoor position. Finally, we present a novel location prediction system based on neural embeddings, and a soft-attention mechanism, which is able to predict user\u2019s next location with 67\\% accuracy.}, language = {English}, number = {14}, journal = {Sensors}, author = {Bilbao Jayo, Aritz and Almeida, Aitor and Sergi, Ilaria and Montanaro, Teodoro and Fasano, Luca and Emaldi, Mikel and Patrono, Luigi}, month = jul, year = {2021}, keywords = {AI for health, Artificial Intelligence, BD4QoL, Behavior modelling, Behavior prediction, FuturAAL, Intelligent Environments, IoT, JCR3.576, Machine learning, Q1, activity recognition, indoor navigation, location systems}, pages = {4839}, } ']

[u' @inproceedings{bilbao_jayo_lightweight_2021, address = {Split, Croatia}, title = {A lightweight semantic-location system for indoor and outdoor behavior modelling}, booktitle = {Proceedings of the 6th {International} {Conference} on {Smart} and {Sustainable} {Technologies}}, author = {Bilbao Jayo, Aritz and Cantero, Xabier and Almeida, Aitor and Fasano, Luca and Montanaro, Teodoro and Sergi, Ilaria and Patrono, Luigi}, month = sep, year = {2021}, keywords = {AAL, AI for health, Ambient Assisted Living, BD4QoL, BLE, BLE beacons, FuturAAL, Indoor Positioning, Intelligent Environments, Machine learning, Outdoor positioning, Smartphone, Smartwatch, artificial intelligence, behavior modelling, cancer, head and neck cancer}, } ']

[u' @article{bilbao_jayo_improving_2021, title = {Improving political discourse analysis on {Twitter} with context analysis}, issn = {2169-3536}, doi = {10.1109/ACCESS.2021.3099093}, abstract = {In this study, we propose a new approach to perform political discourse analysis in social media platforms based on a widely used political categorisation schema in the field of political science, namely, the Comparative Manifestos Project\u2019s category schema. This categorisation schema has been traditionally used to perform content analysis in political manifestos, giving a code that indicates the domain or category of each of the phrases in the manifestos. Therefore, in this work we propose the application of this political discourse analysis technique in Twitter, using as training data of 100 publicly available annotated political manifestos in English with around 85,000 annotated sentences. Furthermore, we also analyse the improvement that using 5,000 annotated tweets could provide to the performance of the political discourse classifier already trained with political manifestos. Finally, we have analysed the 2016 United States presidential elections on Twitter using the proposed approach. As our main finding, we have been able to conclude that both datasets (political manifestos and annotated tweets) can be combined in order to achieve better results, achieving improvements in the F-Measure of more than 15 points. Moreover, we have also analysed if contextual information such as the previous tweet or the political affiliation of the transmitter could improve classifier\u2019s performance as it has already been proven for manifestos classification, introducing a novel method for political parties representation and finding that adding the previous tweet or the political leaning as contextual data does improve its performance.}, journal = {IEEE Access}, author = {Bilbao Jayo, Aritz and Almeida, Aitor}, year = {2021}, keywords = {Annotations, Artificial Intelligence, Computational linguistics, Data analysis, JCR3.367, Machine learning, NLP, Natural language processing, Q2, Social networking (online), Text analysis, Voting, political discourse, politics, social network analysis, social networks}, pages = {1--1}, } ']

[u' @article{bermejo_embedding-based_2021, title = {Embedding-based real-time change point detection with application to activity segmentation in smart home time series data}, volume = {185}, issn = {0957-4174}, url = {https://www.sciencedirect.com/science/article/pii/S0957417421010344}, doi = {10.1016/j.eswa.2021.115641}, abstract = {Human activity recognition systems are essential to enable many assistive applications. Those systems can be sensor-based or vision-based. When sensor\u2026}, language = {en}, urldate = {2021-07-29}, journal = {Expert Systems with Applications}, author = {Bermejo, Unai and Almeida, Aitor and Bilbao Jayo, Aritz and Azkune, Gorka}, month = dec, year = {2021}, keywords = {AI for health, Data analysis, JCR6.954, Q1, activity recognition, artificial intelligence, behavior modelling, change point detection, embeddings, futuraal, intelligent environments, machine learning, smart home, transfer learning}, pages = {115641}, } ']

[u' @article{almeida_bd4qol_2021, title = {{BD4QoL}, mejorando la calidad de vida de supervivientes de cancer de cabeza y cuello}, issn = {2171-858x}, journal = {Revista Ingenier\xeda Deusto}, author = {Almeida, Aitor and Bilbao Jayo, Aritz and Cantero}, month = jan, year = {2021}, keywords = {AI for health, activity recognition, artificial intelligence, bd4qol, behavior modelling, cancer}, } ']

[u' @inproceedings{lopez-perez_digital_2021, address = {Virtual Conference}, title = {Digital health to support head and neck cancer survivors}, booktitle = {Proceedings of the {International} {Conference} on {Biomedical} and {Health} {Informatics} {BHI} 2021}, author = {L\xf3pez-P\xe9rez, Laura and Garcia-Betances, Rebeca I. and Martin Garrido, Juan Carlos and Bilbao Jayo, Aritz and Almeida, Aitor and Cavalieri, Stefano and Filippidou, Despina Elizabeth and Manos, Anastassios and Martinelli, Elena and Sanchez, Moises and Poliwoda, Peter and Mercalli, Franco and Cabrera-Umpi\xe9rrez, Mar\xeda Fernanda and Arredondo, Mar\xeda Teresa and Licitra, Lisa and Fico, Giussepe}, month = jul, year = {2021}, keywords = {AI for health, Artificial Intelligence, BD4QoL, Behavior modelling, cancer, head and neck cancer, machine learning}, } ']

[u' @article{irizar-arrieta_addressing_2020, title = {Addressing {Behavioural} {Technologies} {Through} the {Human} {Factor}: {A} {Review}}, volume = {8}, issn = {2169-3536}, shorttitle = {Addressing {Behavioural} {Technologies} {Through} the {Human} {Factor}}, url = {https://ieeexplore.ieee.org/document/9035412/}, doi = {10.1109/ACCESS.2020.2980785}, abstract = {Energy-efficiency related research has reached a growing interest in recent years due to the imminent scarcity of non-renewable resources in our environment and the impending impacts their usage have on our environment. Thus, facing the reduction of energy waste and management has become a pivotal issue in our society. To cope with energy inefficiency, the scientific research community has identified the promotion of people\u2019s behaviour change as a critical field to foster environmental sustainability. However, the body of literature shows a lack of systematic methods and processes to reach a common ground when designing technology for promoting sustainable behaviour change. Therefore, this paper contributes with a thorough review and analysis of state of the art. Firstly, theoretical works related to behaviour change are collected and studied to clarify their main concepts and theories. Secondly, the different technologies, processes, methods and techniques applied in the field are reviewed to find diverse strategies in the application of the previously explained theoretical domains. Moreover, a wide range of systems developed to improve energy efficiency through human behaviour change is analysed (from augmented objects to the Internet of Things, digital applications or websites). Finally, the detected research gaps are listed to guide future research when aiming to raise the awareness of individuals through Information and Communication Technologies.}, urldate = {2020-04-29}, journal = {IEEE Access}, author = {Irizar-Arrieta, Ane and Gomez-Carmona, Oihane and Bilbao-Jayo, Aritz and Casado-Mansilla, Diego and Lopez-De-Ipina, Diego and Almeida, Aitor}, year = {2020}, keywords = {Activity Recognition, Artificial Intelligence, Behaviour change, Behaviour modelling, FuturAAL, ICT, Intelligent Environments, Internet of Things, IoT, JCR3.367, Q2, Sustainability, Sustainable Behaviour Change, machine, machine learning, sentientthings}, pages = {52306--52322}, } ']

[u' @inproceedings{fasano_performance_2020, address = {Split, Croatia}, title = {Performance {Evaluation} of {Indoor} {Positioning} {Systems} based on {Smartphone} and {Wearable} {Device}}, abstract = {Recently, most solutions designed for Ambient Assisting Living systems are based on indoor positioning systems. There are several technologies and approaches to develop indoor tracking and positioning with different advantages and shortcomings. Taking into account as a starting point some limits and issues analyzed in related scientific works focused on smart AAL systems able to improve the life quality of elderly people, this work aims to carry out a performance comparison between two different approaches to track a person in indoor environments. Both a smartphone and a wearable device have been used in our tests, analyzing the differences of each approach.}, booktitle = {Proceedings of the 5th {International} {Conference} on {Smart} and {Sustainable} {Technologies}}, author = {Fasano, Luca and Sergi, Ilaria and Almeida, Aitor and Bilbao Jayo, Aritz and Rametta, Piercosimo and Patrono, Luigi}, month = sep, year = {2020}, keywords = {AAL, AI for health, Ambient Assisted Living, BLE, Indoor Positioning, Intelligent Environments, Internet of Things, Smartphone, Smartwatch, Wearable device, futuraal}, } ']

[u' @inproceedings{almeida_lung_2020, address = {Las Vegas, USA}, title = {Lung {Ultrasound} for {Point}-of-{Care} {COVID}-19 {Pneumonia} {Stratification}: {Computer}-{Aided} {Diagnostics} in a {Smartphone}. {First} {Experiences} {Classifying} {Semiology} from {Public} {Datasets}}, url = {https://2020.ieee-ius.org/}, abstract = {Lung ultrasound (LUS) has demonstrated potential in managing pneumonia patients, and is actively used at the point-of-care in COVID-19 patient stratification. However, image interpretation is presently both time-consuming and operator-dependent. We explore computer-aided diagnostics of pneumonia semiology based on light-weight neural networks (MobileNets). For proof-of-concept, multi-task learning is performed from online available COVID-19 datasets, for which semiology (overall abnormality, B-lines, consolidations and pleural thickening) is annotated by two radiologists. Initial results suggest that individual indications can be classified with good performance in a smartphone. Neural networks may also help to reduce inter-reader variability and objectivize LUS interpretation, especially for early-stage pathological indications.}, booktitle = {Proceedings of the {International} {Ultrasound} {Symposium} 2020}, author = {Almeida, Aitor and Bilbao-Jayo, Aritz and Ruby, Lisa and Rominger, Marga and L\xf3pez-De-Ipi\xf1a, Diego and Dahl, Jeremy and El Kaffas, Ahmed and Sanabria, Sergio}, month = aug, year = {2020}, keywords = {AI for health, Artificial Intelligence, ISI, LUS, POCUS, b-lines, convolutional networks, covid19, image processing, lung ultrasound, machine learning, mobilenet, pneumonia, point-of-care ultrasound, semiology, subpleural consolidations, ultrasound}, } ']

[u' @article{sanchez-corcuera_smart_2019, title = {Smart cities survey: {Technologies}, application domains and challenges for the cities of the future}, volume = {15}, issn = {1550-1477}, shorttitle = {Smart cities survey}, url = {https://doi.org/10.1177/1550147719853984}, doi = {10.1177/1550147719853984}, abstract = {The introduction of the Information and Communication Technologies throughout the last decades has created a trend of providing daily objects with smartness, aiming to make human life more comfortable. The paradigm of Smart Cities arises as a response to the goal of creating the city of the future, where (1) the well-being and rights of their citizens are guaranteed, (2) industry and (3) urban planning is assessed from an environmental and sustainable viewpoint. Smart Cities still face some challenges in their implementation, but gradually more research projects of Smart Cities are funded and executed. Moreover, cities from all around the globe are implementing Smart City features to improve services or the quality of life of their citizens. Through this article, (1) we go through various definitions of Smart Cities in the literature, (2) we review the technologies and methodologies used nowadays, (3) we summarise the different domains of applications where these technologies and methodologies are applied (e.g. health and education), (4) we show the cities that have integrated the Smart City paradigm in their daily functioning and (5) we provide a review of the open research challenges. Finally, we discuss about the future opportunities for Smart Cities and the issues that must be tackled in order to move towards the cities of the future.}, language = {en}, number = {6}, urldate = {2019-06-10}, journal = {International Journal of Distributed Sensor Networks}, author = {S\xe1nchez-Corcuera, Ruben and Nu\xf1ez-Marcos, Adri\xe1n and Sesma-Solance, Jesus and Bilbao-Jayo, Aritz and Mulero, Rub\xe9n and Zulaika, Unai and Azkune, Gorka and Almeida, Aitor}, month = jun, year = {2019}, keywords = {Artificial Intelligence, IF1.151, IoT, Q4, Survey, architecture, co-creation, e-government, futuraal, smart cities}, pages = {1550147719853984}, } ']

[u' @article{bilbao_jayo_automatic_2018, title = {Automatic political discourse analysis with multi-scale convolutional neural networks and contextual data}, issn = {1550-1477}, url = {https://journals.sagepub.com/doi/10.1177/1550147718811827}, doi = {10.1177/1550147718811827}, abstract = {In this article, the authors propose a new approach to automate the analysis of the political discourse of the citizens and public servants, to allow public administrations to better react to their needs and claims. The tool presented in this article can be applied to the analysis of the underlying political themes in any type of text, in order to better understand the reasons behind it. To do so, the authors have built a discourse classifier using multi-scale convolutional neural networks in seven different languages: Spanish, Finnish, Danish, English, German, French, and Italian. Each of the language-specific discourse classifiers has been trained with sentences extracted from annotated parties\u2019 election manifestos. The analysis proves that enhancing the multi-scale convolutional neural networks with context data improves the political analysis results.}, urldate = {2018-11-15}, journal = {International Journal of Distributed Sensor Networks}, author = {Bilbao Jayo, Aritz and Almeida, Aitor}, month = nov, year = {2018}, note = {00001}, keywords = {Artificial Intelligence, NLP, Q3, cnn, convolutional networks, e-rmp, embeddings, jcr1.614, machine learning, natural language processing, political discourse, politics}, } ']

[u' @inproceedings{almeida_embedding-level_2018, address = {Guanzhou, China}, title = {Embedding-level attention and multi-scale convolutional neural networks for behaviour modelling}, doi = {10.1109/SmartWorld.2018.00103}, abstract = {Understanding human behaviour is a central task in intelligent environments. Understanding what the user does and how she does it allows to build more reactive and smart environments. In this paper we present a new approach to interactivity behaviour modelling. This approach is based on the use of multi-scale convolutional neural networks to detect n-grams in action sequences and a novel method of applying soft attention mechanisms at embedding level. The proposed architecture improves our previous architecture based on recurrent networks, obtaining better result predicting the users\u2019 actions.}, author = {Almeida, Aitor and Azkune, Gorka and Bilbao Jayo, Aritz}, month = oct, year = {2018}, keywords = {AI for health, Artificial Intelligence, City4Age, Deep Learning, Intelligent Environments, Neural Networks, attention mechanism, behavior modelling, cnn, convolutional networks, core-b, embeddings, isi, machine learning}, } ']

[u' @inproceedings{bilbao_jayo_political_2018, address = {Melbourne, Australia}, title = {Political discourse classification in social networks using context sensitive convolutional neural networks}, url = {http://www.aclweb.org/anthology/W18-3513}, abstract = {In this study we propose a new approach to analyse the political discourse in online social networks such as Twitter. To do so, we have built a discourse classifier using Convolutional Neural Networks. Our model has been trained using election manifestos annotated manually by political scientists following the Regional Manifestos Project (RMP) methodology. In total, it has been trained with more than 88,000 sentences extracted from more that 100 annotated manifestos. Our approachtakes into account the context of the phrase in order to classify it, like what was previously said and the political affiliation of the transmitter. To improve the classification results we have used a simplified political message taxonomy developed within the Electronic Regional Manifestos Project (E-RMP). Using this taxonomy, we have validated our approach analysing the Twitter activity of the main Spanish political parties during 2015 and 2016 Spanish general election and providing a study of their discourse.}, booktitle = {Proceedings of the {Sixth} {International} {Workshop} on {Natural} {Language} {Processing} for {Social} {Media}}, author = {Bilbao Jayo, Aritz and Almeida, Aitor}, month = jul, year = {2018}, keywords = {NLP, Twitter, cnn, convolutional networks, e-rmp, embeddings, political discourse, politics, social networks}, pages = {76--85}, } ']

[u' @article{bilbao_jayo_promotion_2016, title = {Promotion of active ageing combining sensor and social network data}, volume = {64}, issn = {1532-0464}, url = {http://www.sciencedirect.com/science/article/pii/S1532046416301307}, doi = {10.1016/j.jbi.2016.09.017}, abstract = {The increase of life expectancy in modern society has caused an increase in elderly population. Elderly people want to live independently in their home environment for as long as possible. However, as we age, our physical skills tend to worsen and our social circle tends to become smaller, something that often leads to a considerable decrease of both our physical and social activities. In this paper, we present an AAL framework developed within the SONOPA project, whose objective is to promote active ageing by combining a social network with information inferred using in-home sensors.}, urldate = {2016-10-10}, journal = {Journal of Biomedical Informatics}, author = {Bilbao Jayo, Aritz and Almeida, Aitor and L\xf3pez-de-Ipi\xf1a, Diego}, month = dec, year = {2016}, note = {00001}, keywords = {AI, AI for health, Active ageing, Ambient Assisted Living, Artificial Intelligence, BERT, Context-Aware Computing, Data analysis, Data mining for social networks, Intelligent Environments, Q1, Social networks, cnn, convolutional networks, embeddings, fraseware, jcr2.447, social network analysis, sonopa}, pages = {108--115}, } ']