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- Lambrix, Patrick, et al.
(author)
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A Session-based Approach for Aligning Large Ontologies
- 2013
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In: The Semantic Web: Semantics and Big Data. - Berlin, Heidelberg : Springer Berlin/Heidelberg. - 9783642382871 - 9783642382888 ; , s. 46-60
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Conference paper (peer-reviewed)abstract
- There are a number of challenges that need to be addressed when aligning large ontologies. Previous work has pointed out scalability and efficiency of matching techniques, matching with background knowledge, support for matcher selection, combination and tuning, and user involvement as major requirements. In this paper we address these challenges. Our first contribution is an ontology alignment framework that enables solutions to each of the challenges. This is achieved by introducing different kinds of interruptable sessions. The framework allows partial computations for generating mapping suggestions, partial validations of mappings suggestions and use of validation decisions in (re)computation of mapping suggestions and the recommendation of alignment strategies to use. Further, we describe an implemented system providing solutions to each of the challenges and show through experiments the advantages of the session-based approach.
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2. |
- Lambrix, Patrick, et al.
(author)
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A session-based ontology alignment approach enabling user involvement
- 2017
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In: Semantic Web. - : IOS Press. - 1570-0844 .- 2210-4968. ; 8:2, s. 225-251
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Journal article (peer-reviewed)abstract
- One of the current challenges in ontology alignment is the user involvement in the alignment process. To obtain high-quality alignments user involvement is needed for validation of matching results as well as in the mapping generation process. Further, there is a need for supporting the user in tasks such as matcher selection, combination and tuning.In this paper we introduce a conceptual ontology alignment framework that enables user involvement in a natural way. This is achieved by introducing different kinds of interruptible sessions. The framework allows partial computations for generating mapping suggestions, partial validations of mapping suggestions, recommendations for alignment strategies as well as the use of validation decisions in the (re-)computation of mapping suggestions and the recommendations. Further, we show the feasibility of the approach by implementing a session-based version of an existing system. We also show through experiments the advantages of our approach for ontology alignment as well as for evaluation of ontology alignment strategies.
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3. |
- Laurie, Steven, et al.
(author)
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The RD-Connect Genome-Phenome Analysis Platform : Accelerating diagnosis, research, and gene discovery for rare diseases
- 2022
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In: Human Mutation. - : John Wiley & Sons. - 1059-7794 .- 1098-1004. ; 43:6, s. 717-733
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Journal article (peer-reviewed)abstract
- Rare disease patients are more likely to receive a rapid molecular diagnosis nowadays thanks to the wide adoption of next-generation sequencing. However, many cases remain undiagnosed even after exome or genome analysis, because the methods used missed the molecular cause in a known gene, or a novel causative gene could not be identified and/or confirmed. To address these challenges, the RD-Connect Genome-Phenome Analysis Platform (GPAP) facilitates the collation, discovery, sharing, and analysis of standardized genome-phenome data within a collaborative environment. Authorized clinicians and researchers submit pseudonymised phenotypic profiles encoded using the Human Phenotype Ontology, and raw genomic data which is processed through a standardized pipeline. After an optional embargo period, the data are shared with other platform users, with the objective that similar cases in the system and queries from peers may help diagnose the case. Additionally, the platform enables bidirectional discovery of similar cases in other databases from the Matchmaker Exchange network. To facilitate genome-phenome analysis and interpretation by clinical researchers, the RD-Connect GPAP provides a powerful user-friendly interface and leverages tens of information sources. As a result, the resource has already helped diagnose hundreds of rare disease patients and discover new disease causing genes.
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4. |
- Pena, Jose, et al.
(author)
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Contributions of LiU/ADIT to Chain Graphs
- 2012
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In: Advances in secure and networked information systems. - Link : Linköping University Electronic Press. - 9789175197173 - 9789175197166 ; , s. 121-130
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Book chapter (other academic/artistic)abstract
- This book contains contributions by current and former colleagues and PhD students of professor Nahid Shahmehri in celebration of her 60th birthday. Although it would be difficult to cover the full range of her academic contributions, we have at least been able to hint the importance and the breadth of her work. We have chosen the title ‘Advances in Secure and Networked Information Systems - The ADIT Perspective’ as many of the contributions of Nahid and her group have been in these areas, given a fairly broad interpretation of “networked information systems”. In this collection we have gathered both republications of past work as well as newly written articles.
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5. |
- Tan, He, et al.
(author)
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Building frame-based corpus on the basis of ontological domain knowledge
- 2011
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In: Proceedings of the Workshop on BioNLP. - : Association for Computational Linguistics. - 9781932432916 ; , s. 74-82, s. 74-82
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Conference paper (peer-reviewed)abstract
- Semantic Role Labeling (SRL) plays a key role in many NLP applications. The development of SRL systems for the biomedical domain is frustrated by the lack of large domain-specific corpora that are labeled with semantic roles. Corpus development has been very expensive and time-consuming. In this paper we propose a method for building frame-based corpus on the basis of domain knowledge provided by ontologies. We believe that ontologies, as a structured and semantic representation of domain knowledge, can instruct and ease the tasks in building the corpora. In the paper we present a corpus built by using the method. We compared it to BioFrameNet, and examined the gaps between the semantic classification of the target words in the domain-specific corpus and in FrameNet and Prop-Bank/VerbNet.
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6. |
- Tan, He, et al.
(author)
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Ontology-driven Construction of Corpus with Frame Semantics Annotations
- 2012
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In: Computational Linguistics and Intelligent Text Processing13th International Conference, CICLing 2012, New Delhi, India, March 11-17, 2012, Proceedings, Part I. - Berlin, Heidelberg : Springer. - 9783642286032 - 9783642286049 ; , s. 54-65
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Conference paper (peer-reviewed)abstract
- Semantic Role Labeling plays a key role in many text mining applications. The development of SRL systems for the biomedical domain is frustrated by the lack of large domain specific corpora that are labeled with semantic roles. In this paper we proposed a method for building corpus that are labeled with semantic roles for the domain of biomedicine. The method is based on the theory of frame semantics, and uses domain knowledge provided by ontologies. By using the method, we have built a corpus for transport events strictly following the domain knowledge provided by GO biological process ontology. We compared one of our frames to a BioFrameNet frame. We also examined the gaps between the semantic classification of the target words in this domain-specific corpus and in FrameNet and PropBank/VerbNet data. The successful corpus construction demonstrates that ontologies, as a formal representation of domain knowledge, can instruct us and ease all the tasks in building this kind of corpus. Furthermore, ontological domain knowledge leads to well-defined semantics exposed on the corpus, which will be very valuable in text mining applications.
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7. |
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8. |
- Tan, He, et al.
(author)
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Ontology-Driven Construction of Domain Corpus with Frame Semantics Annotations
- 2012
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In: Computational linguistics and intelligent text processing. - Berlin, Heidelberg : Springer Berlin/Heidelberg. - 9783642286032 - 9783642286049 ; , s. 54-65
-
Conference paper (peer-reviewed)abstract
- Semantic Role Labeling plays a key role in many text mining applications. The development of SRL systems for the biomedical domain is frustrated by the lack of large domain specific corpora that are labeled with semantic roles. In this paper we proposed a method for building corpus that are labeled with semantic roles for the domain of biomedicine. The method is based on the theory of frame semantics, and uses domain knowledge provided by ontologies. By using the method, we have built a corpus for transport events strictly following the domain knowledge provided by GO biological process ontology. We compared one of our frames to a BioFrameNet frame. We also examined the gaps between the semantic classification of the target words in this domain-specific corpus and in FrameNet and PropBank/VerbNet data. The successful corpus construction demonstrates that ontologies, as a formal representation of domain knowledge, can instruct us and ease all the tasks in building this kind of corpus. Furthermore, ontological domain knowledge leads to well-defined semantics exposed on the corpus, which will be very valuable in text mining applications.
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