Abstract
Time is an essential component for the analysis of medical data, and the sentiment beneath the temporal information is intrinsically connected with the medical reasoning tasks. The present paper introduces the problem of identifying temporal information as well as tracking of the sentiments/emotions according to the temporal situations from the interviews of cancer patients. A supervised method has been used to identify the medical events using a list of temporal words along with various syntactic and semantic features. We also analyzed the sentiments of the patients with respect to the time-bins with the help of dependency based sentiment analysis techniques and several Sentiment lexicons. We have achieved the maximum accuracy of 75.38% and 65.06% in identifying the temporal and sentiment information, respectively.
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Patra, B.G., Ghosh, N., Das, D., Bandyopadhyay, S. (2015). Identifying Temporal Information and Tracking Sentiment in Cancer Patients’ Interviews. In: Gelbukh, A. (eds) Computational Linguistics and Intelligent Text Processing. CICLing 2015. Lecture Notes in Computer Science(), vol 9042. Springer, Cham. https://doi.org/10.1007/978-3-319-18117-2_14
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DOI: https://doi.org/10.1007/978-3-319-18117-2_14
Publisher Name: Springer, Cham
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