Peter von Etter

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Global medical and epidemic surveillance is an essential function of Public Health agencies, whose mandate is to protect the public from major health threats. To perform this function effectively one requires timely and accurate medical information from a wide range of sources. In this work we present a freely accessible system designed to monitor disease(More)
This paper describes an on-going effort to combine Information Retrieval (IR) and Information Extraction (IE) technologies, to leverage the benefits provided by both approaches to add value for the end-user, as compared with IR or IE in isolation. The main aim of the combined system is to pool together information from multiple sources to improve the(More)
This paper presents ongoing work on application of Information Extraction (IE) technology to domain of Public Health, in a real-world scenario. A central issue in IE is the quality of the results. We present two novel points. First, we distinguish the criteria for quality: the objective criteria that measure correctness of the system’s analysis in(More)
There is currently a paucity of publicly available NLP tools to support analysis of Russian-language text. This especially concerns higher-level applications, such as Information Extraction. We present work on tools for information extraction from text in Russian in the domain of on-line news. On the lower level we employ the AOT toolkit for natural(More)
PULS is an information extraction system based on NLP. The system is controlled by a number of domain-specic knowledge bases and performs the extraction by matching a series of patterns on the input text. The system uses a simple document-local heuristic to assign condence to the extracted records. An evaluation of this heuristic shows that it identies(More)
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