Abstract
Compression of sentences in Facebook posts and Twitter is one of the important tasks for automatic summarization of social media text. The task can be formally defined as transformation of sentence into precise form by preserving the original meaning of the sentence. In this paper, we propose an approach for compressing sentences from Facebook English posts by dropping those words who contribute very less importance to the overall meaning of sentences. We develop one parallel corpus of Facebook English posts and corresponding compressed sentences for our research task. We also report evaluation result of our approach through experiments on develop dataset.
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Rudrapal, D., Datta, M., Datta, A., Das, P., Das, S. (2020). An Approach to Compress English Posts from Social Media Texts. In: Behera, H., Nayak, J., Naik, B., Pelusi, D. (eds) Computational Intelligence in Data Mining. Advances in Intelligent Systems and Computing, vol 990. Springer, Singapore. https://doi.org/10.1007/978-981-13-8676-3_8
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DOI: https://doi.org/10.1007/978-981-13-8676-3_8
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