Key-phrase based classification of public health web pages.
This paper describes and evaluates the public health web pages classification model based on key phrase extraction and matching. Easily extendible both in terms of new classes as well as the new language this method proves to be a good solution for text classification faced with the total lack of training data. To evaluate the proposed solution we have used a small collection of public health related web pages created by a double blind manual classification. Our experiments have shown that by choosing the adequate threshold value the desired value for either precision or recall can be achieved.
Health on the Net Foundation, Geneva, Switzerland.
Ljiljana
L
Dolamic
Célia
C
Boyer
D001185:Artificial Intelligence; D054626:Consumer Health Information / Q000145:classification*; D004282:Documentation / Q000145:classification*; D009323:Natural Language Processing; D010363:Pattern Recognition, Automated / Q000379:methods*; D011634:Public Health / Q000145:classification*; D040442:Public Health Informatics; D012660:Semantics; D061108:Social Media; D013557:Switzerland; D009626:Terminology as Topic; D018875:Vocabulary, Controlled