“John is an excellent manager. He's capable of taking complex, multi-team problems and telling everyone exactly what they need to do to contribute to the ideal outcome. Then he follows up and makes sure they do it. But more than that, he's an excellent mentor. Anyone in his employ can count on him to answer day-to-day questions and provide meaningful critical feedback, but also show them how to start building the skills necessary to be the person answering questions and providing feedback to others. John makes his teams more productive, and the people on those teams just plain better.”
About
Activity
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A year ago, we at Gro correctly predicted that the sharp food price increases seen in preceding years would begin to moderate, although some…
A year ago, we at Gro correctly predicted that the sharp food price increases seen in preceding years would begin to moderate, although some…
Liked by John De Oliveira
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Watching the Juan Sequeda (of Data.World) interview on Cognitive Revolution. Companies that are serious about being successful with large language…
Watching the Juan Sequeda (of Data.World) interview on Cognitive Revolution. Companies that are serious about being successful with large language…
Shared by John De Oliveira
Experience & Education
Licenses & Certifications
Volunteer Experience
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Advisory Board
Business Analytics, Le Moyne College
- Present 4 years 11 months
Education
Assist in the success of the program by reviewing the curriculum and program, recommending educational topics, and bringing real world scenarios to students to prepare them for some of the challenges they will face.
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Advisory Board
MS Analytics at Texas A&M University
- 5 years 11 months
Education
Provide program administrators objective advice about the needs of industry, gauging future trends, seeking new strategies for marketing and recruiting initiatives, and identifying topics that should be addressed in the curriculum.
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Director
Semantic Web Austin
- 4 years 1 month
Science and Technology
The Semantic Web Austin group was founded by Juan Sequeda and John De Oliveira in early 2008. The group bootstrapped its way close to 100 hands-on active members, hosted numerous events including the first US Linked Data Tutorial by Tom Heath from Talis, the first US VoCamp (semantic vocabulary camp), and attracted international attention.
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Executive Director
The Cyc Foundation
- 6 years 10 months
Science and Technology
The Cyc Foundation was a not-for-profit organization dedicated to the enrichment and utilization of the open source portions of the Cyc knowledge base—the world’s largest repository of machine-readable, common-sense knowledge.
Publications
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An Introduction to the Syntax and Content of Cyc
AAAI Spring Symposium on Formalizing and Compiling Background Knowledge and Its Applications to Knowledge Representation and Question Answering, Stanford
From the beginning, a primary goal of the Cyc project has been to build a large knowledge base containing a store of formalized background knowledge suitable for supporting reasoning in a variety of domains. In this paper, we will discuss the portion of Cyc technology that has been released in open source form as OpenCyc, provide examples of the content available in ResearchCyc, and discuss their utility for the future development of fully formalized knowledge bases.
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OpenCyc Ontology
Cycorp
OpenCyc is the open source version of the Cyc(r) technology, the world's largest and most complete general knowledge base and reasoning engine. Intended audience: Information Technology, Science/Research, Education, Developers. Related categories: Artificial Intelligence.
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Talking with Computers about the Future We Shall Share
Proceedings. Twenty-Third Annual International Computer Software and Applications Conference
The time has never been more fitting than now to prepare for a future involving intelligent machines since recent advances have cleared the way for a massive effort that will finally give computers a basic understanding of our world. As computers begin to acquire "common sense" intelligence, they will be transformed from information appliances into helpers, coaches and secretaries. But the most important role for computers and people over the next 5 to 10 years will be that of strident…
The time has never been more fitting than now to prepare for a future involving intelligent machines since recent advances have cleared the way for a massive effort that will finally give computers a basic understanding of our world. As computers begin to acquire "common sense" intelligence, they will be transformed from information appliances into helpers, coaches and secretaries. But the most important role for computers and people over the next 5 to 10 years will be that of strident. Computers and people will be partners in a dialogue to understand our world and guide it to a peaceful and prosperous future.
Patents
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Systems and methods for the creation, update and use of models in finding and analyzing content
Issued 10558666
Embodiments of a search system that provides knowledge based searching of content based on a knowledge model created from the content being searched are disclosed. Embodiments of such search systems may build a model of entitles and relationships representing the collective knowledge contained in a set of content analyzed. When a search is performed on content the model may be leveraged to improve the accuracy, relevance and recall of the search.
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Method and system for correlating social media conversations
Issued US 10003560
A conversation correlation system is configured to associate social signals with conversations and group the conversations into topic clusters. The topic clusters for different days are linked together to form conversation streams. The conversation streams may identify conversation topics within ecosystems and identify changes in conversation topics over time. Topic labels may be generated for the topic clusters that better describe conversation topics. In one example, the topic labels may be…
A conversation correlation system is configured to associate social signals with conversations and group the conversations into topic clusters. The topic clusters for different days are linked together to form conversation streams. The conversation streams may identify conversation topics within ecosystems and identify changes in conversation topics over time. Topic labels may be generated for the topic clusters that better describe conversation topics. In one example, the topic labels may be generated using a mutual information topic distribution model.
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Systems and methods for the creation, update and use of models in finding and analyzing content
Filed US 20170011092
Embodiments of a search system that provides knowledge based searching of content based on a knowledge model created from the content being searched are disclosed. Embodiments of such search systems may build a model of entities and relationships representing the collective knowledge contained in a set of content analyzed. When a search is performed on content the model may be leveraged to improve the accuracy, relevance and recall of the search.
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Method and system for temporal correlation of social signals
Issued US 9288123
A social analytic system may collect social signals from different social network accounts. The social signals may be associated with different ecosystems. Time series data may be generated from the social signals and the time series data may be filtered to remove at least some generic or unrelated trends. Different data sets from the time series data may be associated with different ecosystem metrics. The social analytic system may compare different filtered time series data sets to identify…
A social analytic system may collect social signals from different social network accounts. The social signals may be associated with different ecosystems. Time series data may be generated from the social signals and the time series data may be filtered to remove at least some generic or unrelated trends. Different data sets from the time series data may be associated with different ecosystem metrics. The social analytic system may compare different filtered time series data sets to identify different ecosystem events. For example, the comparisons may be used to identify highly correlated ecosystem metrics and ecosystem anomalies, and predict ecosystem events.
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Apparatus and method for model-based social analytics
Issued US 9251530
A model based social analytic system collects social signals from social network accounts for different companies and constituents. The social signals can be used to benchmark social network performance for different contextual dimensions, such as industries, companies, brands, etc. Conversations may be identified in the signals and the types of constituents participating in the conversations may be identified. Analytics can then be determined for the contextual dimensions based on the related…
A model based social analytic system collects social signals from social network accounts for different companies and constituents. The social signals can be used to benchmark social network performance for different contextual dimensions, such as industries, companies, brands, etc. Conversations may be identified in the signals and the types of constituents participating in the conversations may be identified. Analytics can then be determined for the contextual dimensions based on the related conversations and the types of constituents participating in the conversations.
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