Browsing Data Science Institute (Scholarly Articles) by Author "http://dx.doi.org/10.13039/501100001602"

Now showing items 1-17 of 17

    • Biological applications of knowledge graph embedding models 

      Mohamed, Sameh K.; Nounu, Aayah; Nováček, Vít (Oxford University Press (OUP), 2020-02-17)
      Complex biological systems are traditionally modelled as graphs of interconnected biological entities. These graphs, i.e. biological knowledge graphs, are then processed using graph exploratory approaches to perform different ...

    • The colloquial WordNet: Extending Princeton WordNet with neologisms 

      McCrae, John P.; Wood, Ian D.; HIcks, Amanda (Springer International Publishing, 2017-05-27)
      Princeton WordNet is one of the most important resources for natural language processing, but has not been updated for over ten years and is not suitable for analyzing the fast moving language as used on social media. We ...

    • A comparison of emotion annotation approaches for text 

      Wood, Ian D.; McCrae, John P.; Andryushechkin, Vladimir; Buitelaar, Paul (MDPI, 2018-05-11)
      While the recognition of positive/negative sentiment in text is an established task with many standard data sets and well developed methodologies, the recognition of a more nuanced affect has received less attention: there ...

    • Discovering protein drug targets using knowledge graph embeddings 

      Mohamed, Sameh K.; Nováček, Vít; Nounu, Aayah (Oxford University Press, 2019-08-01)
      Motivation Computational approaches for predicting drug-target interactions (DTIs) can provide valuable insights into the drug mechanism of action. DTI predictions can help to quickly identify new promising (on-target) ...

    • Improving data workflow systems with cloud services and use of open data for bioinformatics research 

      Karim, Md. Rezaul; Michel, Audrey; Zappa, Achille; Baranov, Pavel; Sahay, Ratnesh; Rebholz-Schuhmann, Dietrich (Oxford University Press, 2017-04-16)
      Data workflow systems (DWFSs) enable bioinformatics researchers to combine components for data access and data analytics, and to share the final data analytics approach with their collaborators. Increasingly, such systems ...

    • Intent classification by the use of automatically generated knowledge graphs 

      Arcan, Mihael; Manjunath, Sampritha; Robin, Cécile; Verma, Ghanshyam; Pillai, Devishree; Sarkar, Simon; Dutta, Sourav; Assem, Haytham; McCrae, John P.; Buitelaar, Paul (MDPI, 2023-05-12)
      Intent classification is an essential task for goal-oriented dialogue systems for automatically identifying customers¿ goals. Although intent classification performs well in general settings, domain-specific user goals can ...

    • Knowledge graph driven approach to represent video streams for spatiotemporal event pattern matching in complex event processing 

      Yadav, Piyush; Salwala, Dhaval; Das, Dibya Prakash; Curry, Edward (World Scientific Publishing, 2020)
      Complex Event Processing (CEP) is an event processing paradigm to perform real-time analytics over streaming data and match high-level event patterns. Presently, CEP is limited to process structured data stream. Video ...

    • A linked data visualiser for finite element biosimulations 

      Mehdi, Muntazir; Khan, Yasar; Jares, Joao; Freitas, Andre; Jha, Alok Kumar; Sakellarios, Antonis; Sahay, Ratnesh (World Scientific Publishing, 2016)
      Biosimulation models are used to understand the multiple or different causative factors that cause impairment in human organs. Finite Element Method (FEM) provide a mathematical framework to simulate dynamic biological ...

    • Query-driven video event processing for the internet of multimedia things 

      Yadav, Piyush; Salwala, Dhaval; Arruda Pontes, Felipe; Dhingra, Praneet; Curry, Edward (VLDB Endowment, 2021-08)
      Advances in Deep Neural Network (DNN) techniques have revolutionized video analytics and unlocked the potential for querying and mining video event patterns. This paper details GNOSIS, an event processing platform to ...

    • A random walk model for entity relatedness 

      Torres-Tramón, Pablo; Hayes, Conor (Springer Verlag, 2018-10-31)
      Semantic relatedness is a critical measure for a wide variety of applications nowadays. Numerous models, including path-based, have been proposed for this task with great success in many applications during the last few ...

    • SAFE: SPARQL federation over RDF data cubes with access control 

      Khan, Yasar; Saleem, Muhammad; Mehdi, Muntazir; Hogan, Aidan; Mehmood, Qaiser; Rebholz-Schuhmann, Dietrich; Sahay, Ratnesh (BioMed Central, 2017-02-01)
      Several query federation engines have been proposed for accessing public Linked Open Data sources. However, in many domains, resources are sensitive and access to these resources is tightly controlled by stakeholders; ...

    • Social impact assessment of scientist from mainstream news and weblogs 

      Timilsina, Mohan; Khawaja, Waqas; Davis, Brian; Taylor, Mike; Hayes, Conor (Springer Verlag, 2017-10-14)
      Research policy makers, funding agencies, universities and government organizations evaluate research output or impact based on the traditional citation count, peer review, h-index and journal impact factors. These impact ...

    • Synergy between embedding and protein functional association networks for drug label prediction using harmonic function 

      Timilsina, Mohan; Mc Kernan, Declan Patrick; Yang, Haixuan; d’Aquin, Mathieu (ACM and IEEE, 2020-10-16)
      Semi-Supervised Learning (SSL) is an approach to machine learning that makes use of unlabeled data for training with a small amount of labeled data. In the context of molecular biology and pharmacology, one can take advantage ...

    • Toward distributed, global, deep learning using IoT devices 

      Sudharsan, Bharath; Patel, Pankesh; Breslin, John; Ali, Muhammad Intizar; Mitra, Karan; Dustdar, Schahram; Rana, Omer; Jayaraman, Prem Prakash; Ranjan, Rajiv (Institute of Electrical and Electronics Engineers (IEEE), 2021-07-20)
      Deep learning (DL) using large scale, high-quality IoT datasets can be computationally expensive. Utilizing such datasets to produce a problem-solving model within a reasonable time frame requires a scalable distributed ...

    • Towards an integrative approach for making sense distinctions 

      McCrae, John P.; Fransen, Theodorus; Ahmadi, Sina; Buitelaar, Paul; Goswami, Koustava (Frontiers Media, 2022-02-07)
      Word senses are the fundamental unit of description in lexicography, yet it is rarely the case that different dictionaries reach any agreement on the number and definition of senses in a language. With the recent rise in ...

    • Towards precision medicine: discovering novel gynecological cancer biomarkers and pathways using linked data 

      Jha, Alokkumar; Khan, Yasar; Mehdi, Muntazir; Karim, Md Rezaul; Mehmood, Qaiser; Zappa, Achille; Rebholz-Schuhmann, Dietrich; Sahay, Ratnesh (BioMed Central, 2017-09-19)
      Next Generation Sequencing (NGS) is playing a key role in therapeutic decision making for the cancer prognosis and treatment. The NGS technologies are producing a massive amount of sequencing datasets. Often, these datasets ...

    • Where to search top-K biomedical ontologies? 

      Oliveira, Daniela; Butt, Anila Sahar; Haller, Armin; Rebholz-Schuhmann, Dietrich; Sahay, Ratnesh (Oxford University Press, 2018-03-20)
      Motivation Searching for precise terms and terminological definitions in the biomedical data space is problematic, as researchers find overlapping, closely related and even equivalent concepts in a single or multiple ...