Tag: #CMCRC

JOINT APPOSITION EXTRACTION WITH SYNTACTIC AND SEMANTIC CONSTRAINTS

A study by CMCRC researchers presents a fresh look at extracting apposition from large collections of news, web and broadcast text in order to turn unstructured news stories into “computable data”. News is about interactions between entities ‐ people, places and organisations ‐ and understanding stories requires interpreting the entities in them and their attributes.

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PIONEERING VISUALIZATION FRAMEWORK MAKES THE PICTURE CLEARER

Researchers produce a new framework, StreamEB, which could revolutionise the visual analysis of data and graph streams. Dr Quan Nguyen CMCRC PhD graduate U. of Sydney  Prof Peter Eades CMCRC Research Leader U. of Sydney   High velocity data streams such as trading data have become ubiquitous since the 1990s and graph streaming is becoming

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MULTI-FUND DATA ANALYTICS TARGETS ENHANCED VALUE-FOR-MONEY IN HEALTHCARE SERVICES

Governments as well as health and accident compensation insurers are grappling to improve health outcomes while keeping spiralling costs under control. These seemingly irreconcilable goals require a careful balance of policy to help stem the tide of ever increasing costs in the health industry. Dr Uma Srinivasan CMC Insurance Solutions CMC Lead Scientist Keywords: Health insurance,

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ANALYSIS OF LAGIC & SOLVENCY II’S IMPACT ON LIFE INSURERS

Solvency II is a European Union (EU) legislative program that introduces a harmonised insurance regulatory regime across the region. The program is one of the first insurance regulations in the world to follow the Basel Accord approach, with a 3-pillar structure that covers capital requirements, risk management and disclosure requirements. In Australia, the Life and

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