Browsing Data Science Institute by Author "Nováček, Vít"
Now showing items 1-20 of 26
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Aiding the Data Integration in Medicinal Settings by Means of Semantic Technologies
Nováček, Vít; Handschuh, Siegfried (Semantic Technology Institutes International, 2007)The paper introduces basic features of a novel ontology integration framework that explicitly takes the dynamics and data-intensiveness of many practical application scenarios into account. We motivate our research partially ... -
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 ... -
CORAAL - Towards Deep Exploitation of Textual Resources in Life Sciences
Nováček, Vít; Groza, Tudor; Handschuh, Siegfried (Springer Verlag, 2009)Prominent biomedical literature search tools like ScienceDirect, PubMed Central or MEDLINE allow for efficient retrieval of resources based on key words. Due to vast amounts of data available in life sciences, key word ... -
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) ... -
Drug target discovery using knowledge graph embeddings
Mohamed, Sameh K.; Nováček, Vít; Nounu, Aayah (Association for Computing Machinery, 2019-04-08)The field of drug discovery has entered a plateau stage lately. It is increasingly more expensive and time-demanding to introduce new drugs into the market. One of the main reasons is the slow progress in finding novel ... -
Dynamic Integration of Medical Ontologies in Large Scale
Nováček, Vít; Handschuh, Siegfried (ACM Press, 2007) -
Dynamic Ontology Lifecycle Scenario in Translational Medicine
Nováček, Vít; Handschuh, Siegfried (Oxford University Press, 2007)In this paper, we present a healthcare¿oriented vision of dynamic ontology lifecycle that has been recently developed within Knowledge Web ¿ EU Network of Excellence aimed at transition of Semantic Web technologies to ... -
EUREEKA: Deepening the Semantic Web by More Efficient Emergent Knowledge Representation and Processing
Nováček, Vít (CEUR-WS, 2008)One of the major Semantic Web challenges is the knowledge acquisition bottleneck. New content on the web is produced much faster than the respective machine readable annotations, while a scalable knowledge extraction ... -
Extending Community Ontology Using Automatically Generated Suggestions
Nováček, Vít; Dabrowski, Maciej; Kruk, Sebastian Ryszard; Handschuh, Siegfried (AAAI Press, 2007)In this paper we propose an ontology (formal knowledge base) creation methodology based on integrating external ontologies into the one developed by a community of the do- main experts. We present the MarcOntX agent, a ... -
Eye of the Tiger
Nováček, Vít; Groza, Tudor; Handschuh, Siegfried; Decker, Stefan (2009) -
Facilitating prediction of adverse drug reactions by using knowledge graphs and multi-label learning models
Muñoz, Emir; Nováček, Vít; Vandenbussche, Pierre-Yves (Oxford University Press (OUP), 2017-08-18)Timely identification of adverse drug reactions (ADRs) is highly important in the domains of public health and pharmacology. Early discovery of potential ADRs can limit their effect on patient lives and also make drug ... -
Identifying equivalent relation paths in knowledge graphs
Mohamed, Sameh K.; Muñoz, Emir; Nováček, Vít; Vandenbussche, Pierre-Yves (Springer Verlag, 2017-06-19)Relation paths are sequences of relations with inverse that allow for complete exploration of knowledge graphs in a two-way unconstrained manner. They are powerful enough to encode complex relationships between entities ... -
Imprecise Empirical Ontology Refinement: Application to Taxonomy Acquisition
Nováček, Vít (INSTICC, 2007)The significance of uncertainty representation has become obvious in the Semantic Web community recently. This paper presents new results of our research on uncertainty incorporation into ontologies created automatically ... -
Infrastructure for Dynamic Knowledge Integration -- Automated Biomedical Ontology Extension Using Textual Resources
Nováček, Vít; Handschuh, Siegfried; Davis, Brian (Elsevier, 2008)We present a novel ontology integration technique that explicitly takes the dynamics and data-intensiveness of e-health and biomedicine application domains into account. Changing and growing knowledge, possibly contained ... -
Invited Talk: Can We Deal with Emergent Knowledge Yet?
Nováček, Vít (VSE Prague, 2010)This overview paper briefly describes problems we need to tackle if we want to meaningfully and efficiently process emergent knowledge. By this term we essentially mean knowledge continually emerging in a bottom-up manner ... -
Knowledge base completion using distinct subgraph paths
Mohamed, Sameh K.; Nováček, Vít; Vandenbussche, Pierre-Yves (ACM, 2018-04-09)Graph feature models facilitate efficient and interpretable predictions of missing links in knowledge bases with network structure (i.e. knowledge graphs). However, existing graph feature models-e.g. Subgraph Feature ... -
Knowledge-Based Search for Oncological Literature: Technical Architecture and User Perspectives
Nováček, Vít; Groza, Tudor; Handschuh, Siegfried (IEEE, 2009)Using the current state of the art in life science publication search (e.g., PubMed), one can efficiently search for resources containing particular key-words or their combinations. It is impossible to search for abstract ... -
Link prediction using multi part embeddings
Mohamed, Sameh K.; Nováček, Vít (NUI Galway, 2019-06-02)Knowledge graph embeddings models are widely used to provide scalable and efficient link prediction for knowledge graphs. They use different techniques to model embeddings interactions, where their tensor factorisation ... -
A Non-traditional Inference Paradigm for Learned Ontologies
Nováček, Vít (CEUR Workshop proceedings, 2007) -
Regularizing knowledge graph embeddings via equivalence and inversion axioms
Minervini, Pasquale; Costabello, Luca; Muñoz, Emir; Nováček, Vít; Vandenbussche, Pierre-Yves (Springer Verlag, 2017-12-30)Learning embeddings of entities and relations using neural architectures is an effective method of performing statistical learning on large-scale relational data, such as knowledge graphs. In this paper, we consider the ...