UMBC ebiquity
2017 December

Archive for December, 2017

Videos of ISWC 2017 talks

December 16th, 2017, by Tim Finin, posted in iswc, Semantic Web

Videos of almost all of the talks from the 16th International Semantic Web Conference (ISWC) held in Vienna in 2017 are online at videolectures.net. They include 89 research presentations, two keynote talks, the one-minute madness event and the opening and closing ceremonies.

Jennifer Sleeman receives AI for Earth grant from Microsoft

December 12th, 2017, by Tim Finin, posted in AI, Earth science, Machine Learning, NLP, NLP

Jennifer Sleeman receives AI for Earth grant from Microsoft

Visiting Assistant Professor Jennifer Sleeman (Ph.D. ’17)  has been awarded a grant from Microsoft as part of its ‘AI for Earth’ program. Dr. Sleeman will use the grant to continue her research on developing algorithms to model how scientific disciplines such as climate change evolve and predict future trends by analyzing the text of articles and reports and the papers they cite.

AI for Earth is a Microsoft program aimed at empowering people and organizations to solve global environmental challenges by increasing access to AI tools and educational opportunities, while accelerating innovation. Via the Azure for Research AI for Earth award program, Microsoft provides selected researchers and organizations access to its cloud and AI computing resources to accelerate, improve and expand work on climate change, agriculture, biodiversity and/or water challenges.

UMBC is among the first grant recipients of AI for Earth, first launched in July 2017. The grant process was a competitive and selective process and was awarded in recognition of the potential of the work and power of AI to accelerate progress.

As part of her dissertation research, Dr. Sleeman developed algorithms using dynamic topic modeling to understand influence and predict future trends in a scientific discipline. She applied this to the field of climate change and used assessment reports of the Intergovernmental Panel on Climate Change (IPCC) and the papers they cite. Since 1990, an IPCC report has been published every five years that includes four separate volumes, each of which has many chapters. Each report cites tens of thousands of research papers, which comprise a correlated dataset of temporally grounded documents. Her custom dynamic topic modeling algorithm identified topics for both datasets and apply cross-domain analytics to identify the correlations between the IPCC chapters and their cited documents. The approach reveals both the influence of the cited research on the reports and how previous research citations have evolved over time.

Dr. Sleeman’s award is part of an inaugural set of 35 grants in more than ten countries for access to Microsoft Azure and AI technology platforms, services and training.  In an post on Monday, AI for Earth can be a game-changer for our planet, Microsoft announced its intent to put $50 million over five years into the program, enabling grant-making and educational trainings possible at a much larger scale.

More information about AI for Earth can be found on the Microsoft AI for Earth website.

Link Before You Share: Managing Privacy Policies through Blockchain

December 4th, 2017, by Tim Finin, posted in Blockchain, Policy, Privacy

Link Before You Share: Managing Privacy Policies through Blockchain

Agniva Banerjee, and Karuna Pande Joshi, Link Before You Share: Managing Privacy Policies through Blockchain, 4th International Workshop on Privacy and Security of Big Data (PSBD 2017), in conjunction with 2017 IEEE International Conference on Big Data, 4 December 2017.

With the advent of numerous online content providers, utilities and applications, each with their own specific version of privacy policies and its associated overhead, it is becoming increasingly difficult for concerned users to manage and track the confidential information that they share with the providers. We have developed a novel framework to automatically track details about how a user’s PII is stored, used and shared by the provider. We have integrated our data privacy ontology with the properties of blockchain, to develop an automated access-control and audit mechanism that enforces users’ data privacy policies when sharing their data across third parties. We have also validated this framework by implementing a working system LinkShare. In this paper, we describe our framework on detail along with the LinkShare system. Our approach can be adopted by big data users to automatically apply their privacy policy on data operations and track the flow of that data across various stakeholders.

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