ºÝºÝߣshows by User: CraigKnoblock / http://www.slideshare.net/images/logo.gif ºÝºÝߣshows by User: CraigKnoblock / Tue, 25 Sep 2018 21:26:34 GMT ºÝºÝߣShare feed for ºÝºÝߣshows by User: CraigKnoblock Learning to Adapt to Sensor Changes and Failures /slideshow/learning-to-adapt-to-sensor-changes-and-failures/116550958 2017-08-15-ijcai-iot-v4-180925212635
Invited talk at the IJCAI Workshop on AI for Internet of Things, August 19, 2017]]>
Invited talk at the IJCAI Workshop on AI for Internet of Things, August 19, 2017]]> Tue, 25 Sep 2018 21:26:34 GMT /slideshow/learning-to-adapt-to-sensor-changes-and-failures/116550958 CraigKnoblock@slideshare.net(CraigKnoblock) Learning to Adapt to Sensor Changes and Failures CraigKnoblock Invited talk at the IJCAI Workshop on AI for Internet of Things, August 19, 2017 <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/2017-08-15-ijcai-iot-v4-180925212635-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> Invited talk at the IJCAI Workshop on AI for Internet of Things, August 19, 2017
Learning to Adapt to Sensor Changes and Failures from Craig Knoblock
]]> 850 3 https://cdn.slidesharecdn.com/ss_thumbnails/2017-08-15-ijcai-iot-v4-180925212635-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 From Artwork to Cyber Attacks: Lessons Learned in Building Knowledge Graphs using Semantic Web Technologies /slideshow/from-artwork-to-cyber-attacks-lessons-learned-in-building-knowledge-graphs-using-semantic-web-technologies/89299311 2018-03-01-us2ts-keynote-v5-180301192013
Over the last few years we have been building domain-specific knowledge graphs for a variety of real-world problems, including creating virtual museums, combating human trafficking, identifying illegal arms sales, and predicting cyber attacks. We have developed a variety of techniques to construct such knowledge graphs, including techniques for extracting data from online sources, aligning the data to a domain ontology, and linking the data across sources. In his talk I will present these techniques and describe our experience in applying Semantic Web technologies to build knowledge graphs for real-world problems. ]]>
Over the last few years we have been building domain-specific knowledge graphs for a variety of real-world problems, including creating virtual museums, combating human trafficking, identifying illegal arms sales, and predicting cyber attacks. We have developed a variety of techniques to construct such knowledge graphs, including techniques for extracting data from online sources, aligning the data to a domain ontology, and linking the data across sources. In his talk I will present these techniques and describe our experience in applying Semantic Web technologies to build knowledge graphs for real-world problems. ]]> Thu, 01 Mar 2018 19:20:13 GMT /slideshow/from-artwork-to-cyber-attacks-lessons-learned-in-building-knowledge-graphs-using-semantic-web-technologies/89299311 CraigKnoblock@slideshare.net(CraigKnoblock) From Artwork to Cyber Attacks: Lessons Learned in Building Knowledge Graphs using Semantic Web Technologies CraigKnoblock Over the last few years we have been building domain-specific knowledge graphs for a variety of real-world problems, including creating virtual museums, combating human trafficking, identifying illegal arms sales, and predicting cyber attacks. We have developed a variety of techniques to construct such knowledge graphs, including techniques for extracting data from online sources, aligning the data to a domain ontology, and linking the data across sources. In his talk I will present these techniques and describe our experience in applying Semantic Web technologies to build knowledge graphs for real-world problems. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/2018-03-01-us2ts-keynote-v5-180301192013-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> Over the last few years we have been building domain-specific knowledge graphs for a variety of real-world problems, including creating virtual museums, combating human trafficking, identifying illegal arms sales, and predicting cyber attacks. We have developed a variety of techniques to construct such knowledge graphs, including techniques for extracting data from online sources, aligning the data to a domain ontology, and linking the data across sources. In his talk I will present these techniques and describe our experience in applying Semantic Web technologies to build knowledge graphs for real-world problems.
From Artwork to Cyber Attacks: Lessons Learned in Building Knowledge Graphs using Semantic Web Technologies from Craig Knoblock
]]> 1511 4 https://cdn.slidesharecdn.com/ss_thumbnails/2018-03-01-us2ts-keynote-v5-180301192013-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 Automatic Spatio-temporal Indexing to Integrate and Analyze the Data of an Organization /slideshow/automatic-spatiotemporal-indexing-to-integrate-and-analyze-the-data-of-an-organization/81765587 2017-11-07-urbangis-171108170015
Paper presented at UrbanGIS 2017 – International Workshop on Smart Cities and Urban Analytics on Nov 7, 2017.]]>
Paper presented at UrbanGIS 2017 – International Workshop on Smart Cities and Urban Analytics on Nov 7, 2017.]]> Wed, 08 Nov 2017 17:00:15 GMT /slideshow/automatic-spatiotemporal-indexing-to-integrate-and-analyze-the-data-of-an-organization/81765587 CraigKnoblock@slideshare.net(CraigKnoblock) Automatic Spatio-temporal Indexing to Integrate and Analyze the Data of an Organization CraigKnoblock Paper presented at UrbanGIS 2017 – International Workshop on Smart Cities and Urban Analytics on Nov 7, 2017. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/2017-11-07-urbangis-171108170015-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> Paper presented at UrbanGIS 2017 – International Workshop on Smart Cities and Urban Analytics on Nov 7, 2017.
Automatic Spatio-temporal Indexing to Integrate and Analyze the Data of an Organization from Craig Knoblock
]]> 647 1 https://cdn.slidesharecdn.com/ss_thumbnails/2017-11-07-urbangis-171108170015-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 Lessons Learned in Building Linked Data for the American Art Collaborative /CraigKnoblock/lessons-learned-in-building-linked-data-for-the-american-art-collaborative 2017-10-23-aac-paper-v2-171027190804
ºÝºÝߣs for the paper presented at the 2017 International Semantic Web Conference (ISWC) in Vienna Austria on Oct 23. Paper is available here: https://iswc2017.semanticweb.org/wp-content/uploads/papers/MainProceedings/382.pdf]]>
ºÝºÝߣs for the paper presented at the 2017 International Semantic Web Conference (ISWC) in Vienna Austria on Oct 23. Paper is available here: https://iswc2017.semanticweb.org/wp-content/uploads/papers/MainProceedings/382.pdf]]> Fri, 27 Oct 2017 19:08:04 GMT /CraigKnoblock/lessons-learned-in-building-linked-data-for-the-american-art-collaborative CraigKnoblock@slideshare.net(CraigKnoblock) Lessons Learned in Building Linked Data for the American Art Collaborative CraigKnoblock ºÝºÝߣs for the paper presented at the 2017 International Semantic Web Conference (ISWC) in Vienna Austria on Oct 23. Paper is available here: https://iswc2017.semanticweb.org/wp-content/uploads/papers/MainProceedings/382.pdf <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/2017-10-23-aac-paper-v2-171027190804-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> ºÝºÝߣs for the paper presented at the 2017 International Semantic Web Conference (ISWC) in Vienna Austria on Oct 23. Paper is available here: https://iswc2017.semanticweb.org/wp-content/uploads/papers/MainProceedings/382.pdf
Lessons Learned in Building Linked Data for the American Art Collaborative from Craig Knoblock
]]> 366 6 https://cdn.slidesharecdn.com/ss_thumbnails/2017-10-23-aac-paper-v2-171027190804-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 Extracting, Aligning, and Linking Data to Build Knowledge Graphs /slideshow/extracting-aligning-and-linking-data-to-build-knowledge-graphs/77306727 2017-06-25-building-kgs-no-hidden-170627163219
Invited Talk at the Workshop on Industrial Knowledge Graphs as part of the 2017 Web Science Conference. June 25, 2017]]>
Invited Talk at the Workshop on Industrial Knowledge Graphs as part of the 2017 Web Science Conference. June 25, 2017]]> Tue, 27 Jun 2017 16:32:18 GMT /slideshow/extracting-aligning-and-linking-data-to-build-knowledge-graphs/77306727 CraigKnoblock@slideshare.net(CraigKnoblock) Extracting, Aligning, and Linking Data to Build Knowledge Graphs CraigKnoblock Invited Talk at the Workshop on Industrial Knowledge Graphs as part of the 2017 Web Science Conference. June 25, 2017 <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/2017-06-25-building-kgs-no-hidden-170627163219-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> Invited Talk at the Workshop on Industrial Knowledge Graphs as part of the 2017 Web Science Conference. June 25, 2017
Extracting, Aligning, and Linking Data to Build Knowledge Graphs from Craig Knoblock
]]> 1985 7 https://cdn.slidesharecdn.com/ss_thumbnails/2017-06-25-building-kgs-no-hidden-170627163219-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 Assigning semantic labels to data sources /slideshow/assigning-semantic-labels-to-data-sources/63513480 eswcpresentationramnandansk-160628074503
Presented at the 12th Extended Semantic Web Conference, ESWC 2015.]]>
Presented at the 12th Extended Semantic Web Conference, ESWC 2015.]]> Tue, 28 Jun 2016 07:45:03 GMT /slideshow/assigning-semantic-labels-to-data-sources/63513480 CraigKnoblock@slideshare.net(CraigKnoblock) Assigning semantic labels to data sources CraigKnoblock Presented at the 12th Extended Semantic Web Conference, ESWC 2015. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/eswcpresentationramnandansk-160628074503-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> Presented at the 12th Extended Semantic Web Conference, ESWC 2015.
Assigning semantic labels to data sources from Craig Knoblock
]]> 639 7 https://cdn.slidesharecdn.com/ss_thumbnails/eswcpresentationramnandansk-160628074503-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 A scalable architecture for extracting, aligning, linking, and visualizing multi-int data /slideshow/a-scalable-architecture-for-extracting-aligning-linking-and-visualizing-multiint-data/63513246 2015-04-20-spie-dig-160628073713
Presented at the Conference on the Next Generation Analyst III. SPIE, 9499, 2015.]]>
Presented at the Conference on the Next Generation Analyst III. SPIE, 9499, 2015.]]> Tue, 28 Jun 2016 07:37:13 GMT /slideshow/a-scalable-architecture-for-extracting-aligning-linking-and-visualizing-multiint-data/63513246 CraigKnoblock@slideshare.net(CraigKnoblock) A scalable architecture for extracting, aligning, linking, and visualizing multi-int data CraigKnoblock Presented at the Conference on the Next Generation Analyst III. SPIE, 9499, 2015. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/2015-04-20-spie-dig-160628073713-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> Presented at the Conference on the Next Generation Analyst III. SPIE, 9499, 2015.
A scalable architecture for extracting, aligning, linking, and visualizing multi-int data from Craig Knoblock
]]> 413 5 https://cdn.slidesharecdn.com/ss_thumbnails/2015-04-20-spie-dig-160628073713-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 Building and Using a Knowledge Graph to Combat Human Trafficking /slideshow/building-and-using-a-knowledge-graph-to-combat-human-trafficking/63512920 2015-10-10-dig-iswc-02-pdf-160628072658
Presented at the 14th International Semantic Web Conference (ISWC 2015). Paper was selected Best Application Paper.]]>
Presented at the 14th International Semantic Web Conference (ISWC 2015). Paper was selected Best Application Paper.]]> Tue, 28 Jun 2016 07:26:58 GMT /slideshow/building-and-using-a-knowledge-graph-to-combat-human-trafficking/63512920 CraigKnoblock@slideshare.net(CraigKnoblock) Building and Using a Knowledge Graph to Combat Human Trafficking CraigKnoblock Presented at the 14th International Semantic Web Conference (ISWC 2015). Paper was selected Best Application Paper. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/2015-10-10-dig-iswc-02-pdf-160628072658-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> Presented at the 14th International Semantic Web Conference (ISWC 2015). Paper was selected Best Application Paper.
Building and Using a Knowledge Graph to Combat Human Trafficking from Craig Knoblock
]]> 989 5 https://cdn.slidesharecdn.com/ss_thumbnails/2015-10-10-dig-iswc-02-pdf-160628072658-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 From Virtual Museums to Peacebuilding: Creating and Using Linked Knowledge /slideshow/2014-robert-s-engelmore-memorial-lecture-award/37731593 2014-07-29-englemore-award-v10-140806125208-phpapp01
Companies, such as Google and Microsoft, are building web-scale linked knowledge bases for the purpose of indexing and searching the Web, but these efforts do not address the problem of building accurate, fine-grained, deep knowledge bases for specific application domains. We are developing an integration framework, called Karma, which supports the rapid, end-to-end construction of such linked knowledge bases. In this talk I will describe machine-learning techniques for mapping new data sources to a domain model and linking the data across sources. I will also present several applications of this technology, including building virtual museums and integrating data sources for peacebuilding. ]]>
Companies, such as Google and Microsoft, are building web-scale linked knowledge bases for the purpose of indexing and searching the Web, but these efforts do not address the problem of building accurate, fine-grained, deep knowledge bases for specific application domains. We are developing an integration framework, called Karma, which supports the rapid, end-to-end construction of such linked knowledge bases. In this talk I will describe machine-learning techniques for mapping new data sources to a domain model and linking the data across sources. I will also present several applications of this technology, including building virtual museums and integrating data sources for peacebuilding. ]]> Wed, 06 Aug 2014 12:52:08 GMT /slideshow/2014-robert-s-engelmore-memorial-lecture-award/37731593 CraigKnoblock@slideshare.net(CraigKnoblock) From Virtual Museums to Peacebuilding: Creating and Using Linked Knowledge CraigKnoblock Companies, such as Google and Microsoft, are building web-scale linked knowledge bases for the purpose of indexing and searching the Web, but these efforts do not address the problem of building accurate, fine-grained, deep knowledge bases for specific application domains. We are developing an integration framework, called Karma, which supports the rapid, end-to-end construction of such linked knowledge bases. In this talk I will describe machine-learning techniques for mapping new data sources to a domain model and linking the data across sources. I will also present several applications of this technology, including building virtual museums and integrating data sources for peacebuilding. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/2014-07-29-englemore-award-v10-140806125208-phpapp01-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> Companies, such as Google and Microsoft, are building web-scale linked knowledge bases for the purpose of indexing and searching the Web, but these efforts do not address the problem of building accurate, fine-grained, deep knowledge bases for specific application domains. We are developing an integration framework, called Karma, which supports the rapid, end-to-end construction of such linked knowledge bases. In this talk I will describe machine-learning techniques for mapping new data sources to a domain model and linking the data across sources. I will also present several applications of this technology, including building virtual museums and integrating data sources for peacebuilding.
From Virtual Museums to Peacebuilding: Creating and Using Linked Knowledge from Craig Knoblock
]]> 2535 5 https://cdn.slidesharecdn.com/ss_thumbnails/2014-07-29-englemore-award-v10-140806125208-phpapp01-thumbnail.jpg?width=120&height=120&fit=bounds presentation 000000 http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 Semantics for Big Data Integration and Analysis /slideshow/semantics-for-big-data-integration-and-analysis/37110354 2013-11-15-bigkarma-fss-140717205220-phpapp01
Much of the focus on big data has been on the problem of processing very large sources. There is an equally hard problem of how to normalize, integrate, and transform the data from many sources into the format required to run large-scale anal- ysis and visualization tools. We have previously developed an approach to semi-automatically mapping diverse sources into a shared domain ontology so that they can be quickly com- bined. In this paper we describe our approach to building and executing integration and restructuring plans to support analysis and visualization tools on very large and diverse datasets.]]>
Much of the focus on big data has been on the problem of processing very large sources. There is an equally hard problem of how to normalize, integrate, and transform the data from many sources into the format required to run large-scale anal- ysis and visualization tools. We have previously developed an approach to semi-automatically mapping diverse sources into a shared domain ontology so that they can be quickly com- bined. In this paper we describe our approach to building and executing integration and restructuring plans to support analysis and visualization tools on very large and diverse datasets.]]> Thu, 17 Jul 2014 20:52:20 GMT /slideshow/semantics-for-big-data-integration-and-analysis/37110354 CraigKnoblock@slideshare.net(CraigKnoblock) Semantics for Big Data Integration and Analysis CraigKnoblock Much of the focus on big data has been on the problem of processing very large sources. There is an equally hard problem of how to normalize, integrate, and transform the data from many sources into the format required to run large-scale anal- ysis and visualization tools. We have previously developed an approach to semi-automatically mapping diverse sources into a shared domain ontology so that they can be quickly com- bined. In this paper we describe our approach to building and executing integration and restructuring plans to support analysis and visualization tools on very large and diverse datasets. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/2013-11-15-bigkarma-fss-140717205220-phpapp01-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> Much of the focus on big data has been on the problem of processing very large sources. There is an equally hard problem of how to normalize, integrate, and transform the data from many sources into the format required to run large-scale anal- ysis and visualization tools. We have previously developed an approach to semi-automatically mapping diverse sources into a shared domain ontology so that they can be quickly com- bined. In this paper we describe our approach to building and executing integration and restructuring plans to support analysis and visualization tools on very large and diverse datasets.
Semantics for Big Data Integration and Analysis from Craig Knoblock
]]> 2017 3 https://cdn.slidesharecdn.com/ss_thumbnails/2013-11-15-bigkarma-fss-140717205220-phpapp01-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 A Semantic Approach to Retrieving, Linking, and Integrating Heterogeneous Geospatial Data /slideshow/ijcai-presentationv04/28009324 ijcai-presentation-v04-131107104521-phpapp02
Ying Zhang, Yao-Yi Chang, Pedro Szekely, and Craig A. Knoblock, A Semantic Approach to Retrieving, Linking, and Integrating Heterogeneous Geospatial Data, Proceedings of the 2013 IJCAI Workshop on Semantic Cities, 2013]]>
Ying Zhang, Yao-Yi Chang, Pedro Szekely, and Craig A. Knoblock, A Semantic Approach to Retrieving, Linking, and Integrating Heterogeneous Geospatial Data, Proceedings of the 2013 IJCAI Workshop on Semantic Cities, 2013]]> Thu, 07 Nov 2013 10:45:21 GMT /slideshow/ijcai-presentationv04/28009324 CraigKnoblock@slideshare.net(CraigKnoblock) A Semantic Approach to Retrieving, Linking, and Integrating Heterogeneous Geospatial Data CraigKnoblock Ying Zhang, Yao-Yi Chang, Pedro Szekely, and Craig A. Knoblock, A Semantic Approach to Retrieving, Linking, and Integrating Heterogeneous Geospatial Data, Proceedings of the 2013 IJCAI Workshop on Semantic Cities, 2013 <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/ijcai-presentation-v04-131107104521-phpapp02-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> Ying Zhang, Yao-Yi Chang, Pedro Szekely, and Craig A. Knoblock, A Semantic Approach to Retrieving, Linking, and Integrating Heterogeneous Geospatial Data, Proceedings of the 2013 IJCAI Workshop on Semantic Cities, 2013
A Semantic Approach to Retrieving, Linking, and Integrating Heterogeneous Geospatial Data from Craig Knoblock
]]> 957 4 https://cdn.slidesharecdn.com/ss_thumbnails/ijcai-presentation-v04-131107104521-phpapp02-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 Discovering Alignments in Ontologies of Linked Data /CraigKnoblock/ijcai-presentation-v5 ijcai-20presentation-20v5-131107090705-phpapp02
Rahul Parundekar and Craig A. Knoblock and Jose Luis Ambite, Discovering Alignments in Ontologies of Linked Data, Proceedings of the 23rd International Joint Conference on Artificial Intelligence (IJCAI), 2013]]>
Rahul Parundekar and Craig A. Knoblock and Jose Luis Ambite, Discovering Alignments in Ontologies of Linked Data, Proceedings of the 23rd International Joint Conference on Artificial Intelligence (IJCAI), 2013]]> Thu, 07 Nov 2013 09:07:05 GMT /CraigKnoblock/ijcai-presentation-v5 CraigKnoblock@slideshare.net(CraigKnoblock) Discovering Alignments in Ontologies of Linked Data CraigKnoblock Rahul Parundekar and Craig A. Knoblock and Jose Luis Ambite, Discovering Alignments in Ontologies of Linked Data, Proceedings of the 23rd International Joint Conference on Artificial Intelligence (IJCAI), 2013 <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/ijcai-20presentation-20v5-131107090705-phpapp02-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> Rahul Parundekar and Craig A. Knoblock and Jose Luis Ambite, Discovering Alignments in Ontologies of Linked Data, Proceedings of the 23rd International Joint Conference on Artificial Intelligence (IJCAI), 2013
Discovering Alignments in Ontologies of Linked Data from Craig Knoblock
]]> 773 4 https://cdn.slidesharecdn.com/ss_thumbnails/ijcai-20presentation-20v5-131107090705-phpapp02-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 https://cdn.slidesharecdn.com/profile-photo-CraigKnoblock-48x48.jpg?cb=1578910484 http://www.isi.edu/~knoblock https://cdn.slidesharecdn.com/ss_thumbnails/2017-08-15-ijcai-iot-v4-180925212635-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/learning-to-adapt-to-sensor-changes-and-failures/116550958 Learning to Adapt to S... https://cdn.slidesharecdn.com/ss_thumbnails/2018-03-01-us2ts-keynote-v5-180301192013-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/from-artwork-to-cyber-attacks-lessons-learned-in-building-knowledge-graphs-using-semantic-web-technologies/89299311 From Artwork to Cyber ... https://cdn.slidesharecdn.com/ss_thumbnails/2017-11-07-urbangis-171108170015-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/automatic-spatiotemporal-indexing-to-integrate-and-analyze-the-data-of-an-organization/81765587 Automatic Spatio-tempo...