Ponències/Comunicacions de congressos
Recent Submissions
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Semantics for connectivity management in IoT sensing
(Springer Nature, 2021)
Conference report
Open AccessThere are a large number of Internet of Things (IoT) devices that transmit information over the Internet, each with a different data format to denote the same semantic concept. This often leads to data incompatibilities ... -
Improving the extraction of process annotations from text with inter-sentence analysis
(Springer, 2020)
Conference report
Open AccessThe automatic extraction of formal process information from textual descriptions of processes is a challenging problem, but worth exploring, since it enables organizations to align complementary information that talks about ... -
XYZ Monitor: IoT monitoring of infrastructures using microservices
(Springer, 2020)
Conference report
Open AccessOne of the main features of the Internet of Things (IoT) is the ability to collect data from everywhere, convert this data into knowledge, and then use this knowledge to monitor about an undesirable situation. Monitoring ... -
Mining dependencies in large-scale Agile software development projects: A quantitative industry study
(Association for Computing Machinery (ACM), 2021)
Conference report
Open AccessContext: Coordination in large-scale software development is critical yet difficult, as it faces the problem of dependency management and resolution. In this work, we focus on managing requirement dependencies that in Agile ... -
PatternLens: Inferring evolutive patterns from web API usage logs
(Springer, 2021)
Conference report
Open AccessThe use of web Application Programming Interfaces (WAPIs) has experienced a boost in recent years. Developers (i.e., WAPI consumers) are continuously relying on third-party WAPIs to incorporate certain features into their ... -
Improving Web API usage logging
(Springer, 2021)
Conference report
Open AccessA Web API (WAPI) is a type of API whose interaction with its consumers is done through the Internet. While being accessed through the Internet can be challenging, mostly when WAPIs evolve, it gives providers the possibility ... -
Integrating adaptive mechanisms into mobile applications exploiting user feedback
(Springer, 2021)
Conference lecture
Open AccessMobile applications have become a commodity in multiple daily scenarios. Their increasing complexity has led mobile software ecosystems to become heterogeneous in terms of hardware specifications, features and context of ... -
RESim - Automated detection of duplicated requirements in software engineering projects
(CEUR-WS.org, 2020)
Conference report
Open AccessCollaborative software development experience in recent years proves that the management of large sets of requirements has become a critical issue. Among the main problems of requirements engineering, the detection and ... -
Effective and scalable data discovery with NextiaJD
(OpenProceedings, 2021)
Conference lecture
Open AccessWe present NextiaJD, a data discovery system with high predictive performance and computational efficiency. NextiaJD aids data scientists in the discovery of datasets that can be crossed. To that end, it proposes a ranking ... -
Towards scalable data discovery
(OpenProceedings, 2021)
Conference lecture
Open AccessWe study the problem of discovering joinable datasets at scale. We approach the problem from a learning perspective relying on profiles. These are succinct representations that capture the underlying characteristics of the ... -
A data-driven approach to measure the usability of Web APIs
(Institute of Electrical and Electronics Engineers (IEEE), 2020)
Conference report
Open AccessApplication Programming Interfaces (APIs) are means of communication between applications, hence they can be seen as user interfaces, just with different kind of users, i.e., software or computers. However, the very first ... -
Continual lifelong learning in natural language processing: a survey
(Association for Computational Linguistics, 2020)
Conference lecture
Open AccessContinual learning (CL) aims to enable information systems to learn from a continuous data stream across time. However, it is difficult for existing deep learning architectures to learn a new task without largely forgetting ...