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This video was recorded at 11th International Semantic Web Conference (ISWC), Boston 2012. The New York Times committment to Linked Data began over 160 years ago. Starting in 1851, The New York Times has always catalogued its archival articles using a controlled vocabulary of people, places, organizations and descriptors. In 2009 The New York Times started publishing this vocabulary as linked data using semantic web standards. In 2011 The Times announced the launch of several RESTful Semantic APIs. And in late 2012 and early 2013, The Times will migrate its entire process for vocabulary management to a system designed around the principles of Linked Data. In my remarks, I will survey the history of Semantic publishing at The New York Times, outline our semantic strategy, detail the business-case for linked data at The Times and provide an in-depth explanation of our new vocabulary management system.
- Subjects:
- Computing, Data Science and Artificial Intelligence and Management
- Keywords:
- New York times Linked data
- Resource Type:
- Presentation
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Presentation
This video was recorded at 16th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), Washington 2010. Crisis Management and Disaster Recovery have gained immense importance in the wake of recent man and nature inflicted calamities. A critical problem in a crisis situation is how to efficiently discover, collect, organize, search and disseminate real-time disaster information. In this paper, we address several key problems which inhibit better information sharing and collaboration between both private and public sector participants for disaster management and recovery. We design and implement a web based prototype implementation of a Business Continuity Information Network (BCIN) system utilizing the latest advances in data mining technologies to create a user-friendly, Internet-based, information-rich service and acting as a vital part of a company's business continuity process. Specifically, information extraction is used to integrate the input data from different sources; the content recommendation engine and the report summarization module provide users personalized and brief views of the disaster information; the community generation module develops spatial clustering techniques to help users build dynamic community in disasters. Currently, BCIN has been exercised at Miami-Dade County Emergency Management.
- Subjects:
- Computing, Data Science and Artificial Intelligence and Management
- Resource Type:
- Presentation
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