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Presentation
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 4th European Semantic Technology Conference (ESTC), Vienna 2010. Linked Enterprise Data goes beyond Semantic Web by including any data sources in an outside of business processes. The presentation shows how Linked Enterprise Data not only slimline it infrastructure but also enables automatic information logistics to combine process management and information retrieval. It is a way to reduce complexity challenging information growth and process variety and flexibility. Practical examples show the business needs and the implementation of related solutions to enable rationalization and quality assurance.
- Subjects:
- Computing, Data Science and Artificial Intelligence
- Keywords:
- Management information systems Information resources management Linked data
- Resource Type:
- Presentation
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Presentation
This video was recorded at 7th Extended Semantic Web Conference (ESWC), Heraklion 2010. The mission of the Extended Semantic Web Conference (ESWC 2010) is to bring together researchers and practioners dealing with different aspects of semantics on the Web. ESWC2010 builds on the success of the former European Semantic Web Conference series, but seeks to extend its focus by engaging with other communities within and outside ICT, in which semantics can play an important role. At the same time, ESWC2010 is a truly international conference. Semantics of web content, enriched with domain theories (ontologies), data about web usage, natural language processing, etc. will enable a web that provides a qualitatively new level of functionality. It will weave together a large network of human knowledge and make this knowledge machine-processable. Various automated services, based on reasoning with metadata and ontologies, will help the users to achieve their goals by accessing and processing information in machine-understandable form. This network of knowledge systems will ultimately lead to truly intelligent systems, which will be employed for various complex decision-making tasks. Research about web semantics can benefit from ideas and cross-fertilization with many other areas: Artificial Intelligence, Natural Language Processing, Database and Information Systems, Information Retrieval, Multimedia, Distributed Systems, Social Networks, Web Engineering, and Web Science. ESWC2010 will present the latest results in research and applications in its field. The research program will be organised in targeted tracks. In addition, the conference will feature a tutorial program, system descriptions and demos, a posters track, a Ph.D. symposium and a number of collocated workshops. The calls for these events are separate and can be found on the conference Web site (http://www.eswc2010.org/).
- Subjects:
- Computing, Data Science and Artificial Intelligence and Management
- Keywords:
- Industrial management Workflow -- Management
- 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. The problem of optimally managing the collections process by taxation authorities is one of prime importance, not only for the revenue it brings but also as a means to administer a fair taxing system. The analogous problem of debt collections management in the private sector, such as banks and credit card companies, is also increasingly gaining attention. With the recent successes in the applications of data analytics and optimization to various business areas, the question arises to what extent such collections processes can be improved by use of leading edge data modeling and optimization techniques. In this paper, we propose and develop a novel approach to this problem based on the framework of constrained Markov Decision Process (MDP), and report on our experience in an actual deployment of a tax collections optimization system at New York State Department of Taxation and Finance (NYS DTF).
- Subjects:
- Computing, Data Science and Artificial Intelligence and Management
- Keywords:
- Markov processes -- Mathematical models Debt -- Management
- Resource Type:
- Presentation
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