Distributional Semantic Representation in Health Care Text Classification

Barathi Ganesh H. B., M. Anand Kumar, Soman K. P
2016 Forum for Information Retrieval Evaluation  
This paper describes about the our proposed system in the Consumer Health Information Search (CHIS) task. The objective of the task 1 is to classify the sentences in the document into relevant or irrelevant with respect to the query and task 2 is analysing the sentiment of the sentences in the documents with respect to the given query. In this proposed approach distributional representation of text along with its statistical and distance measures are carried over to perform the given tasks as a
more » ... text classification problem. In our experiment, Non -Negative Matrix Factorization utilized to get the distributed representation of the document as well as queries, distance and correlation measures taken as the features and Random Forest Tree utilized to perform the classification. The proposed approach yields 70.19% in task 1 and 34.64% in task 2 as an average accuracy.
dblp:conf/fire/HBMP16a fatcat:bnm5tycthzd3fkywqlzi4jvscm