Query-Based Extractive Text Summarization Using Sense-Oriented Semantic Relatedness Measure

Author:

Rahman NazreenaORCID,Borah BhogeswarORCID

Publisher

Springer Science and Business Media LLC

Subject

Multidisciplinary

Reference208 articles.

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2. Wu, H.C.; Luk, R.W.P.; Wong, K.F.; Kwok, K.L.: Interpreting tf-idf term weights as making relevance decisions. ACM Trans. Inf. Syst. 26(3), 1–37 (2008)

3. Park, S.; Lee, J.-H.; Ahn, C.-M.; Park, T.-S.; Song, J.-W.; Kim, D.-H.: Query-based text summarization using cosine similarity and nmf. In: Proceedings of the Korea Information Processing Society Conference, pp. 473–476. Korea Information Processing Society (2006)

4. Rastogi, H.: Automatic Text Summarization using Soft-Cosine Similarity and Centrality Measures. Ph.D. thesis (2020)

5. Ramos, J. et al.: Using tf-idf to determine word relevance in document queries. In: Proceedings of the First Instructional Conference on Machine Learning, vol. 242, pp. 29–48. Citeseer (2003)

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