Textual Clustering: Towards a More Efficient Descriptors of Texts

Author:

Bokhabrine Ayoub,Biskri Ismaïl,Ghazzali Nadia

Publisher

Springer International Publishing

Reference19 articles.

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2. Agrawal, R., Srikant, R.: Fast algorithms for mining association rules. In: 20th International Conference on Very Large Database, San Francisco, CA, pp. 487–499 (1994)

3. Alghamdi, R.A., Taileb, M., Ameen, M.: A new multimodal fusion method based on association rules mining for image retrieval. 17th IEEE Mediterranean Electrotechnical Conference “MELECON”, pp. 493–499. Beirut, Lebanon (2014)

4. Bahri, E., Lallich, S.: Proposition d’une méthode de classification associative adaptative. 10eme journées Francophones d’Extraction et Gestion des Connaissances, EGC 2010, pp. 501–512 (2010)

5. Charrad, M., Ghazzali, N., Boiteau, V., Niknafs, A.: NbClust: an R package for determining the relevant number of clusters in a data set. J. Stat. Softw. Foundation for Open Access Statistics Press, 61(6) (2014)

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