Animal Disease Event Recognition and Classication

Using Web Data in the Medical Domain 2010.

计算机科学;图书情报档案学

Svitlana Volkova ; Doina Caragea ; William H. Hsu ; Swathi Bujuru

Others  :  http://ceur-ws.org/Vol-572/paper6.pdf
PID  :  40874

来源: CEUR

【 摘 要 】

Monitoring epidemic crises, caused by rapid spread of infectious animal diseases, can be facilitated by the plethora of information about disease-related events that is available online. Therefore, the ability to use this information to perform domain-specific entity recognition and event-related sentence classication, which in turn can support time and space visualization of automatically extracted events, is highly desirable. Towards this goal, we present a rule-based approach to the problem of extracting animal disease-related events from web documents. Our approach relies on the recognition of structured entity tuples, consisting of attributes, which describe events related to animal diseases. The event attributes that we consider include animal diseases, dates, species and geo-referenced locations. We perform disease names and species recognition using an automatically-constructed ontology, dates are extracted using regular expressions, while location are extracted using a conditional random elds tool. The extracted events are further classified as conrmed or suspected based on semantic features, obtained from the e.g., GoogleSets1 and WordNet2. Our preliminary results demonstrate the feasibility of the proposed approach.