Knowledge Base Acceleration KBA -- a track in NISTs TREC 2012
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I am a research scientist at Facebook AI Research. I am interested in the interplay between physics and computation. My work in theoretical physics has focused on the relationship between black holes. And how the laws of physics are related to fundamental limits of computation. Previously, I was a postdoc in the School of Natural Sciences. At the Institute for Advanced Study. at the Center for Theoretical Physics.
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From Answering Engines to Task-completion Engines. PhD position in Conversational AI. The University of Stavanger invites applications for a fully funded PhD position. The successful candidate will work on the design, development, and evaluation of conversational search systems. In particular, the candidate is expected to employ and develop deep learning techniques for understanding natural language requests and generating appropriate responses.
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I observed that trec-kba.org is utilizing the Apache/2.2.14 (Ubuntu) operating system.PAGE TITLE
Knowledge Base Acceleration KBA -- a track in NISTs TREC 2012DESCRIPTION
TREC Knowledge Base Acceleration. Google Freebase Annotation of KBA StreamCorpus. 2014 Evaluation three tasks. 2 Streaming Slot Filling. 3 Accelerate and Create. Given a rich dossier. On a subject,. Filter a stream of documents to. Accelerate users filling in knowledge gaps. KBA ran as an evalution in TREC. For three years 2012, 2013, and 2014. In 2015, it will be succeeded by TREC Dynamic Domain. See TREC KBA overview slides, papers, and truth data here. KBA 2013 had more tasks and more entities.CONTENT
This domain states the following, "Google Freebase Annotation of KBA StreamCorpus." Our analyzers observed that the web page also stated " Filter a stream of documents to." The Website also stated " Accelerate users filling in knowledge gaps. KBA ran as an evalution in TREC. For three years 2012, 2013, and 2014. In 2015, it will be succeeded by TREC Dynamic Domain. See TREC KBA overview slides, papers, and truth data here. KBA 2013 had more tasks and more entities."VIEW OTHER WEB PAGES
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The goal of the TREC Temporal Summarization Track is to develop systems for efficiently monitoring the information associated with an event over time. Specifically, we are interested in developing systems which can broadcast short, relevant, and reliable sentencelength updates about a developing event. To develop algorithms which detect sub-events with low latency,. To model information reliability in the presence of a dynamic corpus,.
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