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An incremental clustering scheme for data de-duplication.

, , и . Data Min. Knowl. Discov., 20 (1): 152-187 (2010)

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Riccardo Mattei

Riccardo Rubbiani

Riccardo Caccavale

Riccardo Satta

Riccardo Nocentini

 

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Clustering of XML Documents by Structure based on Tree Matching and Merging., , , и . SEBD, стр. 314-325. (2004)Jointly modeling and simultaneously discovering topics and clusters in text corpora using word vectors., и . Inf. Sci., (2021)Machine learning techniques for XML (co-)clustering by structure-constrained phrases., и . Inf. Retr. J., 21 (1): 24-55 (2018)Integrating overlapping community discovery and role analysis: Bayesian probabilistic generative modeling and mean-field variational inference., и . Eng. Appl. Artif. Intell., (2020)Modeling Adaptive Hypermedia with an Object-Oriented Approach and XML., , , , и . WebDyn@WWW, том 702 из CEUR Workshop Proceedings, стр. 35-44. CEUR-WS.org, (2002)Hierarchical clustering of XML documents focused on structural components., , , и . Data Knowl. Eng., (2013)Document Clustering and Topic Modeling: A Unified Bayesian Probabilistic Perspective., и . ICTAI, стр. 278-285. IEEE, (2019)Learning Effective XML Classifiers Based on Discriminatory Structures and Nested Content., , и . IC3K, том 348 из Communications in Computer and Information Science, стр. 156-171. Springer, (2011)A unified generative Bayesian model for community discovery and role assignment based upon latent interaction factors., и . ASONAM, стр. 93-100. IEEE Computer Society, (2014)Ask and Ye shall be Answered: Bayesian tag-based collaborative recommendation of trustworthy experts over time in community question answering., и . Inf. Fusion, (ноября 2023)