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Knowledge Graphs and Knowledge Networks: The Story in Brief [article]

Amit Sheth, Swati Padhee, Amelie Gyrard
2020 arXiv   pre-print
The evolution of search engine responses to user queries in the last few years is partly because of the role of KGs such as Google KG.  ...  This article is an attempt to summarize the journey of KG for AI.  ...  of the future challenges requiring domain-specific knowledge extraction.  ... 
arXiv:2003.03623v1 fatcat:zle7g626mzeqrkmobgrr6xtfae

From Knowledge Engineering to Knowledge Management

Nigel Shadbolt, Nick Milton
1999 British Journal of Management  
Knowledge engineers have devised a number of methods to overcome such problems, such as aggregating knowledge from various sources and validating knowledge across sources.  ...  Finally, experts may vary in the validity of the knowledge they can articulate.  ... 
doi:10.1111/1467-8551.00141 fatcat:73mbzoi6ovctpjdzbckrs4ht6e

Knowledge Democratization – A Business User Tutorial To Knowledge Graph Modeling

Ademar Jr. Crotti
2022 Zenodo  
But while the benefits of knowledge graphs have become clear, the road to their implementation has often been long and complex and success has relied on the involvement of seasoned knowledge graph experts  ...  For example, most ontology modeling tools available today target the ontology engineer, thus excluding domain experts and common business users from this process.  ...  data is a time-consuming task, as data might come from different sources Pinpoint your information needs Model your domain Build the user experience Collaboratively define a knowledge model.  ... 
doi:10.5281/zenodo.6512414 fatcat:uxczf5j4ajhcdddfrils2yegsi

Background knowledge in diagnosis

E.T. Keravnou, F. Dams, J. Washbrook, R.M. Dawood, C.M. Hall, D. Shaw
1992 Artificial Intelligence in Medicine  
Acknowledgements The support of the Leverhulme Trust for the SDD project is gratefully acknowledged.  ...  The need for a diagnostic framework to support the explicit integration of background domain knowledge is certainly not specific to the domain of skeletal dysplasias.  ...  These examples use knowledge which is general radiological/clinical knowledge rather than knowledge specific to the domain of skeletal dysplasias.  ... 
doi:10.1016/0933-3657(92)90041-m fatcat:wgxfo4qe2bfrxl6wub3k2h37qe

Knowledge Engineering [chapter]

Nathalie Aussenac-Gilles, Jean Charlet, Chantal Reynaud
2020 A Guided Tour of Artificial Intelligence Research  
It also requires the analysis of what type of knowledge sources is considered, 5 what human-machine interaction is envisaged and more generally the specific end 6 use.  ...  Research 2 in this domain requires to develop studies on the nature of the knowledge and its 3 representation, either the users' knowledge or the knowledge-based system's knowl-4 edge.  ...  of domain 414 experts or experts in modelling for interpreting the results.  ... 
doi:10.1007/978-3-030-06164-7_23 fatcat:qwnssm5ipzdsjagwv24yobdptq

Automatic medical knowledge acquisition using question-answering

Emilie Pasche, Douglas Teodoro, Julien Gobeill, Patrick Ruch, Christian Lovis
2009 Studies in Health Technology and Informatics  
A top precision of 0.64 is reported, which means, for about two third of the knowledge rules of the benchmark, one of the recommended antibiotic was automatically acquired by the rule generation method  ...  These results suggest that a significant fraction of the medical knowledge can be obtained by such an automatic text mining approach.  ...  This experiment has been supported by the EU-IST-FP7 DebugIT project # 712139. The EAGLi question-answering framework has been developed thanks to the SNF Grant # 325230-120758.  ... 
pmid:19745375 fatcat:qnfeybjbufhqzlrfwwy4qgedoq

Knowledge Exploitation from the Web [chapter]

David Riaño, Antonio Moreno, David Isern, Jaime Bocio, David Sánchez, Laureano Jiménez
2004 Lecture Notes in Computer Science  
In the framework of Knowledge Management, the Internet can be a valuable source of information to produce new Knowledge.  ...  By means of a graphical user interface, the user of the system supplies an ontology in RDF to describe the domain of interest, and sets up some predefined parameters in order to constrain the search corpus  ...  Sánchez would like to acknowledge the support of the Departament d'Universitats, Recerca i Societat de la Informació of Catalonia.  ... 
doi:10.1007/978-3-540-30545-3_17 fatcat:vfjo64oq5jblfgntwksam2wnrq

Relevant evidence acquisition and appraisal using knowledge-intensive queries

Muhammad Afzal, Sungyoung Lee
2016 2016 18th International Conference on Advanced Communication Technology (ICACT)  
The construction of knowledge-intensive query is based on the term expansion using domain model, name variants, and terminological variants.  ...  Information needs of the users have grown exponentially with the advent of advancements in information and communication technology.  ...  The limitation of this strategy is the dependency on domain experts, however, it can be resolved by knowledge of domain.  ... 
doi:10.1109/icact.2016.7423528 fatcat:ve4pmvbf5bf77cw2lsr5mgvpea

Combining expert knowledge and knowledge automatically acquired from electronic data sources for continued ontology evaluation and improvement

Claire L. Gordon, Chunhua Weng
2015 Journal of Biomedical Informatics  
infectious disease case scenarios, to generate a compendium of infectious disease knowledge and use it to evaluate the accuracy and coverage of BCIDO.  ...  Guidelines and expert generated scenarios were the richest source of ID concepts and relationships while patient records provided relatively fewer concepts and relationships.  ...  This work was conducted using the Protégé resource, which is supported by grant GM10331601 from the National Institute of General Medical Sciences of the United States National Institutes of Health.  ... 
doi:10.1016/j.jbi.2015.07.014 pmid:26212414 pmcid:PMC4724344 fatcat:imgpnopwwfepbevm5tukcaw6qu

Web Data Knowledge Extraction [article]

Juan M. Tirado, Ovidiu Serban, Qiang Guo, Eiko Yoneki
2016 arXiv   pre-print
The figure of the expert is still needed in many situations where developers do not have the correct background knowledge.  ...  Our methodology differs from similar solutions in its expert-driven design. This design, makes it possible for subject-matter expert to drive the knowledge extraction for a given set of documents.  ...  The research is funded by H2020 DIGIWHIST project (645852). We would like to thank Christopher Ré in Stanford University for valuable input and discussion and NLP group in University of Cambridge.  ... 
arXiv:1603.07534v1 fatcat:zvf55a5xarbjrnbykp7x5n2dfi

Data driven knowledge acquisition method for domain knowledge enrichment in the healthcare

Sujan Perera, Cory Henson, Krishnaprasad Thirunarayan, Amit Sheth, Suhas Nair
2012 2012 IEEE International Conference on Bioinformatics and Biomedicine  
We determine missing relationships between the domain concepts by validating domain knowledge against real world data sources.  ...  fidelity of domain knowledge.  ...  An ontologist may be unaware of the kind of knowledge to gather from a domain expert, and a domain expert may be unaware of the knowledge they should provide to solve the problem in a technically sound  ... 
doi:10.1109/bibm.2012.6392669 dblp:conf/bibm/PereraHTSN12 fatcat:mu4niqabj5grtmzdql24z3qqhm

Knowledge Engineering Method Based on Consensual Knowledge and Trust Computation: The MUSCKA System [chapter]

Fabien Amarger, Jean-Pierre Chanet, Ollivier Haemmerlé, Nathalie Hernandez, Catherine Roussey
2016 Lecture Notes in Computer Science  
The use of these measures has been evaluated on a real case study with experts from the agriculture domain.  ...  We propose a method for building a knowledge base addressing specific issues such as covering an end-users' need and reuse non-ontological sources such as thesauri or classifications.  ...  We want to thank specially the three experts who helped us validate our results by generating the gold standard: Franck Jabot and Vincent Soulignac from Irstea Clermont-Ferrand and Jacques Le Gouis from  ... 
doi:10.1007/978-3-319-40985-6_14 fatcat:2j5napmzhzfbxbbvf7txvjr3ni

Chapter 1: Biomedical Knowledge Integration

Philip R. O. Payne, Fran Lewitter, Maricel Kann
2012 PLoS Computational Biology  
The modern biomedical  ...  , or otherwise verified and validated [17] sources of biomedical knowledge relevant to a domain of interest.  ...  The process of applying sub-language analysis to existing knowledge sources has been empirically validated in numerous areas, including the biomedical domain [50, 51] .  ... 
doi:10.1371/journal.pcbi.1002826 pmid:23300416 pmcid:PMC3531314 fatcat:ahqikyfnyzbd3gcibedad2eyci

Semantics and knowledge organization

Birger Hjørland
2007 Annual Review of Information Science and Technology  
Information scientists may feel safer if they rely on "experts" rather than documents, but relevant documents are written by experts and are equally valid sources, if not more so.  ...  In other words, semantic structures in IS cannot be established simply by the study of natural languages: this also requires domain-specific knowledge.  ...  Appendix Some important kinds of semantic relations that have been presented in the literature:  ... 
doi:10.1002/aris.2007.1440410115 fatcat:fahklxdhsjcnbgnq7uuwbpc5o4

Incorporating Domain Knowledge into Medical NLI using Knowledge Graphs

Soumya Sharma, Bishal Santra, Abhik Jana, Santosh Tokala, Niloy Ganguly, Pawan Goyal
2019 Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)  
In this paper, we explore how to incorporate structured domain knowledge, available in the form of a knowledge graph (UMLS), for the Medical NLI task.  ...  We also experiment with fusing the domain-specific sentiment information for the task.  ...  Acknowledgements The authors would like to acknowledge the funding and support from Samsung Research Institute, Delhi (SRID), India.  ... 
doi:10.18653/v1/d19-1631 dblp:conf/emnlp/SharmaSJTGG19 fatcat:66dxuxugujc5nhjj2oso2wv4dq
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