Behavioral Ontology of Healthy Lifestyle
We have developed the first named-entity recognizer designed for the lifestyle change domain. It aims at enabling smart health applications to recognize relevant concepts.
We created the first ontology for behavioral health (shown below) based on which we developed an NER augmented with lexical resources. Our NER automatically tags words and phrases in sentences with relevant (lifestyle) domain-specific tags. For example, it can tag:
Named-Entity Recognizers (NERs) are an important part of information extraction systems in annotation tasks. Although substantial progress has been made in recognizing domain-independent named entities (e.g. location, organization and person), there is a need to recognize named entities for domain-specific applications in order to extract relevant concepts.
Our first work on the topic is available below:
We created the first ontology for behavioral health (shown below) based on which we developed an NER augmented with lexical resources. Our NER automatically tags words and phrases in sentences with relevant (lifestyle) domain-specific tags. For example, it can tag:
- healthy food
- unhealthy food
- potentially-risky
- healthy activity,
- drugs,
- tobacco,
- alcoholic beverages.
Named-Entity Recognizers (NERs) are an important part of information extraction systems in annotation tasks. Although substantial progress has been made in recognizing domain-independent named entities (e.g. location, organization and person), there is a need to recognize named entities for domain-specific applications in order to extract relevant concepts.
Our first work on the topic is available below:
- U. Yasavur, R. Amini, C. L. Lisetti, and N. Rishe (2013). Ontology-based Named Entity Recognizer for Behavioral Health. In Proceedings of the 26th International FLAIRS Conference, www.aaai.org, (St Petersburg, Florida, USA, May 2013) [PDF].
