Now showing items 490-509 of 544

    • ULD@NUIG at SemEval-2020 Task 9: Generative morphemes with an attention model for sentiment analysis in code-mixed text 

      Goswami, Koustava; Rani, Priya; Chakravarthi, Bharathi Raja; Fransen, Theodorus; McCrae, John P. (International Committee for Computational Linguistics, 2020)
      Code mixing is a common phenomena in multilingual societies where people switch from one language to another for various reasons. Recent advances in public communication over different social media sites have led to an ...
    • Ultra-fast machine learning classifier execution on IoT devices without SRAM consumption 

      Sudharsan, Bharath; Patel, Pankesh; Breslin, John G.; Ali, Muhammad Intizar (Institute of Electrical and Electronics Engineers (IEEE), 2021-05-25)
      With the introduction of edge analytics, IoT devices are becoming smart and ready for AI applications. A few modern ML frameworks are focusing on the generation of small-size ML models (often in kBs) that can directly be ...
    • Uncovering semantic bias in neural network models using a knowledge graph 

      Nikolov, Andriy; d'Aquin, Mathieu (ACM, 2020-10-19)
      While neural networks models have shown impressive performance in many NLP tasks, lack of interpretability is often seen as a disadvantage. Individual relevance scores assigned by post-hoc explanation methods are not ...
    • Understanding Contributor to Developer Turnover Patterns in OSS Projects: A Case Study of Apache Projects 

      Iqbal, Aftab (Hindawi Publishing Corporation, 2014-01-19)
      OSS projects are dynamic in nature. Developers contribute to a project for a certain period of time and later leave the project or join other projects of high interest. Hence, the OSS community always welcomes members who ...
    • Understanding Linked Open Data as a Web-Scale Database 

      Hausenblas, Michael; Karnstedt, Marcel (2010)
      While Linked Open Data (LOD) has gained much attention in the recent years, requirements and the challenges concerning its usage from a database perspective are lacking. We argue that such a perspective is crucial for ...
    • Understanding my city through dashboards. How hard can it be? 

      Vornhagen, Heike; Young, Karen; Zarrouk, Manel (International Federation for Information Processing (IFIP) and eJournal of eDemocracy and Open Government (JeDEM), 2019-09-02)
      This paper describes research into how current city dashboards support users' sensemaking processes. It uses criteria identified in previous research concerning visualisation and applies these to a number of city dashboards ...
    • Understanding the Maturity of Sustainable ICT 

      Curry, Edward; Donnellan, Brian (Springer, 2012)
      Sustainable ICT (SICT) can develop solutions that offer benefits both internally in IT and across the extended enterprise. However, because the field is new and evolving, few guidelines and best practices are available. ...
    • UniStore: Querying a DHT-based Universal Storage 

      Karnstedt, Marcel; Hauswirth, Manfred (2007)
      In recent time, the idea of collecting and combining large public data sets and services became more and more popular. The special characteristics of such systems and the requirements of the participants demand for ...
    • Unsupervised deep language and dialect identification for short texts 

      Goswami, Koustava; Sarkar, Rajdeep; Chakravarthi, Bharathi Raja; Fransen, Theodorus; McCrae, John P. (International Committee on Computational Linguistics, 2020-12)
      Automatic Language Identification (LI) or Dialect Identification (DI) of short texts of closely related languages or dialects, is one of the primary steps in many natural language processing pipelines. Language identification ...
    • Unsupervised Graph-Based Topic Labelling using DBpedia 

      Hulpus, Ioana; Hayes, Conor; Karnstedt, Marcel; Greene, Derek (2013)
      Automated topic labelling brings benefits for users aiming at analysing and understanding document collections, as well as for search engines targetting at the linkage between groups of words and their inherent topics. ...
    • Unsupervised learning for understanding student achievement in a distance learning setting 

      Liu, Shuangyan; d’Aquin, Mathieu (IEEE, 2017-04-25)
      Many factors could affect the achievement of students in distance learning settings. Internal factors such as age, gender, previous education level and engagement in online learning activities can play an important role ...
    • Unsupervised method to analyze playing styles of EPL teams using ball possession-position data 

      Verma, Pranav; Sudharsan, Bharath; Chakravarthi, Bharathi Raja; O'Riordan, Colm; Hill, Seamus (IEEE, 2020-03-06)
      In the English Premier League (EPL) matches, a network of advanced systems gathers sports data in real-time to build a possession-position dataset. In this work, data fields from the sophisticated raw possession-position ...
    • Update Semantics for Interoperability among XML, RDF and RDB - A Case Study of Semantic Presence in CISCO's Unified Presence Systems 

      Ali, Muhammad Intizar; Lopes, Nuno; Mileo, Alessandra (Springer, 2013)
      XSPARQL is a transformation and querying language that provides an integrated access over heterogeneous data sources on the fly. It is an extension of XQuery which supports a subset of SPARQL and SQL to provide unified ...
    • Using domain-specific and collaborative resources for term translation 

      Arcan, Mihael; Buitelaar, Paul; Federmann, Christian (Association for Computational Linguistics, 2012-07)
      In this article we investigate the translation of terms from English into German and vice versa in the isolation of an ontology vocabulary. For this study we built new domainspecific resources from the translation ...
    • Using drug similarities for discovery of possible adverse reactions 

      Muñoz, Emir; Nováček, Vít; Vandenbussche, Pierre-Yves (AMIA, 2017-02-10)
      We propose a new computational method for discovery of possible adverse drug reactions. The method consists of two key steps. First we use openly available resources to semi-automatically compile a consolidated data set ...
    • Using linked data to mine RDF from wikipedia's tables 

      Muñoz, Emir; Hogan, Aidan; Mileo, Alessandra (ACM, 2014)
      The tables embedded in Wikipedia articles contain rich, semi-structured encyclopaedic content. However, the cumulative content of these tables cannot be queried against. We thus propose methods to recover the semantics of ...
    • Using social media data for online television recommendation services at RTÉ Ireland 

      Barraza-Urbina, Andrea; Hromic, Hugo; Heitmann, Benjamin; Hayes, Conor; Hulpus, Ioana (2015-09)
      Raidió Teilifís Éireann (RTÉ) is the public service television and radio broadcaster in Ireland. Through on demand video services, RTÉ allows their users to catch up on television broadcasts via the RTÉ Player. The company ...
    • Using social media for online television adaptation services at RTÉ Ireland 

      Barraza-Urbina, Andrea; Hromic, Hugo; Heitmann, Benjamin; Tamatam, Himasagar; Yañez, Andrea; Hayes, Conor (Insight Centre for Data Analytics, National University of Ireland, Galway, 2016)
      RTÉ (Raidió Teilifís Éireann) is the national provider of Television (TV) and radio in Ireland. RTÉ broadcasts its content online through the RTÉ Player and provides services to interact with its users using social media, ...
    • Using Tags and Clustering to Identify Topic-Relevant Blogs 

      Hayes, Conor (IAAA, 2007)
      The Web has experienced an exponential growth in the use of weblogs or blogs. Blog entries are generally organised using tags, informally defined labels which are increasingly being proposed as a `grassroots¿ answer to ...
    • Utilising knowledge graph embeddings for data-to-text generation 

      Pasricha, Nivranshu; Arcan, Mihael; Buitelaar, Paul (Association for Computational Linguistics, 2020-12-18)
      Data-to-text generation has recently seen a move away from modular and pipeline architectures towards end-to-end architectures based on neural networks. In this work, we employ knowledge graph embeddings and explore their ...