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Knoesis Knowledge Graph Platform (KKGP), Personalized Health Knowledge Graph (PHKG)

Description

In recent years, knowledge graphs (KGs) have been increasingly used by both academia and industry to incorporate semantics into various intelligent applications. However, the creation of these knowledge graphs are mainly done manually with the help of domain experts and/or by using structured knowledge sources such as Wikipedia. Kno.e.sis Knowledge Graph team works on different aspects to improve creation and consumption of knowledge graphs as given below:

• Contextualized knowledge graphs
• Bootstrap domain-specific knowledge graphs by leveraging existing knowledge sources
• Summarization of the knowledge graphs
• Leveraging knowledge graphs to improve NLP applications
• Dynamically evolve knowledge graphs for real-time events such as twitter campaigns
• Question answering on knowledge graphs
• Ontology quality and best practices
• Ontology methodology to reuse ontologies
• Ontology alignment
• Knowledge extraction from ontologies to reuse the domain knowledge already designed in previous domains.
• Semantic interoperability with a focus on ontologies

Knowledge Graphs (KG) for Applications

KG for Healthcare

Leaders: Dr. Saeedeh Shekarpour, Dr. Amelie Gyrard

KG for Internet of Things (IoT)

Leader: Dr. Amelie Gyrard

Ontology Catalogue for Internet of Things with LOV4IoT

Linked Open Vocabularies for Internet of Things (LOV4IoT) references numerous ontology-based IoT projects:
- Almost 500 ontology-based projects for IoT, smart cities, etc.
- Almost 20 domains relevant to IoT referenced such as building, smart grid, smart agriculture, smart transportation, healthcare, etc.
- We provide the LOV4IoT ontology catalogue as an HTML view.
- We also provide the LOV4IoT RDF dataset.
LOV4IoT is an extension of the LOV (linked Open Vocabularies) catalogue.

• Project Demonstrator: Linked Open Vocabularies for Internet of Things (LOV4IoT)
• LOV4IoT refering almost 400 ontology based IoT projects: http://sensormeasurement.appspot.com/?p=ontologies
• LOV4IoT RDF Dataset: http://sensormeasurement.appspot.com/dataset/lov4iot-dataset
• Publications: Here
• Presentation:

• Demo:

Knowledge Extraction for the Web of Things (KE4WoT) Challenge co-located with The Web Conference 2018 (WWW 2018)

KG for Disaster Management

Leader: Hussein Al-Olimat, Shruti Kar

NSF Project: Hazards SEES: Social and Physical Sensing Enabled Decision Support for Disaster Management and Response

Some publications:

1. Shruti Kar, Hussein S. Al-Olimat, Krishnaprasad Thirunarayan, Valerie Shalin, Amit Sheth, and Srinivasan Parthasarathy. "D-record: Disaster Response and Relief Coordination Pipeline". In Proceedings of the ACM SIGSPATIAL International Workshop on Advances in Resilient and Intelligent Cities (ARIC 2018). ACM, 2018.

Teaching: Advanced Topics in Semantic Web

Some slides related to KG:

• Knowlege Graphs (KG) - Advanced Semantic Web Class, Knoesis Lab, Wright State University - Amelie Gyrard, 11 September 2018

• Contextualized Knowlege Graphs from two perspectives Semantic Web and Graph Database with an application in PubChem - Advanced Semantic Web Class, Knoesis Lab, Wright State University - Vinh Nguyen, 25 October 2018

• Health Knowlege Graphs (KG) - Advanced Semantic Web Class, Knoesis Lab, Wright State University - Amelie Gyrard, 2 October 2018

• Linked Open Data (LOD) - Advanced Semantic Web Class, Knoesis Lab, Wright State University - Amelie Gyrard, 2 October 2018

Event Organisation

Contextualized Knowledge Graphs (CKG) Workshop at ISWC 2018

Contextualized Knowledge Graphs (CKG) Workshop co-located with International Semantic Web Conference (ISWC 2018)

Tutorial at CIKM2018

Graphs: In Theory and Practice co-located with 26th ACM International Conference on Information and Knowledge Management (CIKM)

Publication

Knowledge Extraction for the Web of Things (KE4WoT) Challenge at WWW 2018

Knowledge Extraction for the Web of Things (KE4WoT) Challenge co-located with The Web Conference 2018 (WWW 2018)

Talks

• Talk at Ontolog Community: CKG Portal: A knowledge publishing proposal for open knowledge network - Vinh Nguyen, 28 March 2018

• Talk at Ontolog Community: Evolving Open Health Knowledge Network - Amit Sheth, 28 March 2018

Publications

• Swati Padhee, Sarasi Lalithsena and Amit Sheth. "Creating Real-Time Dynamic Knowledge Graphs".International Semantic Web Research School (ISWS) 2018, Bertinoro, Italy;2018
• A. Sheth, S. Perera, S. Wijeratne, and K. Thirunarayan. Knowledge will Propel Machine Understanding of Content: Extrapolating from Current Examples. Proceedings of the 2017 IEEE/WIC/ACM International Conference on Web Intelligence (WI). Leipzig, Germany. ISBN: 978-1-4503-4951-2/17/08.

• Vinh Nguyen, Olivier Bodenreider, and Amit Sheth. Don't like RDF reification?: making statements about statements using singleton property. Proceedings of the 23rd international conference on World wide web. ACM, 2014.

• Gunaratna, K., Thirunarayan, K., & Sheth, A. P. (2015, January). FACES: Diversity-Aware Entity Summarization Using Incremental Hierarchical Conceptual Clustering. In AAAI (pp. 116-122).

• Gunaratna, K., Thirunarayan, K., Sheth, A., & Cheng, G. (2016, May). Gleaning types for literals in rdf triples with application to entity summarization. In International Semantic Web Conference (pp. 85-100). Springer, Cham.

• Gunaratna, Kalpa, et al. Relatedness-based multi-entity summarization. IJCAI: proceedings of the conference. Vol. 2017. NIH Public Access, 2017.

• Shekarpour, S., Marx, E., Auer, S. & Sheth, A. (2017). RQUERY: Rewriting Natural Language Queries on Knowledge Graphs to Alleviate the Vocabulary Mismatch Problem. 31st AAAI Conference on Artificial Intelligence, San Francisco, California.

• Sarasi Lalithsena, Sujan Perera, Pavan Kapanipathi, Amit Sheth. Domain-specific Hierarchical Subgraph Extraction: A Recommendation Use Case. 2017 IEEE International Conference on Big Data (Big Data), Boston, MA, 2017, pp. 666-675. doi: 10.1109/BigData.2017.8257982

• Sarasi Lalithsena, Pavan Kapanipathi and Amit Sheth. Harnessing relationships for domain-specific subgraph extraction: A recommendation use case. 2016 IEEE International Conference on Big Data (Big Data), Washington, DC, 2016, pp. 706-715. doi: 10.1109/BigData.2016.7840663

• Amelie Gyrard, Martin Serrano, Ghislain Atemezing. Semantic Web Methodologies, Best Practices and Ontology Engineering Applied to Internet of Things. IEEE World Forum on Internet of Things (WF-IoT), Milan, Italy, December 14-16, 2015

• Amelie Gyrard, Soumya Kanti Datta Christian Bonnet. A survey and analysis of ontology-based software tools for semantic interoperability in IoT and WoT landscapes. IEEE 4th World Forum on Internet of Things (WF-IoT), 2018

• Amelie Gyrard, Ghislain Atemezing, Christian Bonnet, Karima Boudaoud and Martin Serrano. Reusing and Unifying Background Knowledge for Internet of Things with LOV4IoT. 4rd International Conference on Future Internet of Things and Cloud (FiCloud 2016), 22-24 August 2016, Vienna, Austria

• Amelie Gyrard, Christian Bonnet, Karima Boudaoud and Martin Serrano. LOV4IoT: A second life for ontology-based domain knowledge to build Semantic Web of Things applications. 4rd International Conference on Future Internet of Things and Cloud (FiCloud 2016), 22-24 August 2016, Vienna, Austria

• Amelie Gyrard, Manas Gaur, Krishnaprasad Thirunarayan, Amit Sheth and Saeedeh Shekarpour. Personalized Health Knowledge Graph. 1st Workshop on Contextualized Knowledge Graph (CKG) co-located with International Semantic Web Conference (ISWC), 8-12 October 2018, Monterey, USA.

PhD Thesis

• PhD Thesis: Domain-specific Knowledge Extraction from the Web of Data [Sarasi Lalithsena March 2018]

• PhD Thesis: Semantic Web Foundations for Representing, Reasoning, and Traversing Contextualized Knowledge Graphs [Vinh Nguyen 2017]

Vinh Nguyen PhD Slides:

Vinh Nguyen PhD Video:

Projects or Tools

• Contextualized Knowledge Graph (CKG) community

Online community discussion forum ckg-community@googlegroups.com, https://groups.google.com/forum/#!forum/ckg-community/join

• LOV4IoT project: Ontology catalog for the Internet of Things which comprises an extension for healthcare.
• PerfectO project: Ontology quality and best practices

Team

Faculty:

• Dr. Amit P. Sheth (Kno.e.sis, Wright State University)
• Dr. Krishnaprasad Thirunarayan (Kno.e.sis, Wright State University)

External Collaboration:

• Dr. Saeedeh Shekarpour (University of Dayton, Former Postdoc @ Kno.e.sis)

Post-doc:

• Dr. Amelie Gyrard (Kno.e.sis, Wright State University)

Graduate Students:

• Manas Gaur (Kno.e.sis, Wright State University)
• Swati Padhee (Kno.e.sis, Wright State University)
• Joy Prakash Sain (Kno.e.sis, Wright State University)

Alumni:

• Kalpa Gunaratne (Samsung, Former PhD at Kno.e.sis)
• Vinh Nguyen (National Library of Medicine, Former PhD at Kno.e.sis)
• Sarasi Lalithsena (Former PhD at Kno.e.sis)

References

• Tutorial Getting started with knowledge graphs
• Knowledge Graph Refinement:A Survey of Approaches and Evaluation Methods Paulheim et al. 2016
• Constructing Knowledge Graphs of Depression Huang et al. 2017
• Development and Evaluation of an Obesity Ontology for Social Big Data Analysis Kim et al. 2017
• Google Knowledge Graph:

• Jamie Taylor's Keynote at ISWC 2017. He manages the Schema Team for Google’s Knowledge Graph.