{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,9,7]],"date-time":"2024-09-07T23:19:58Z","timestamp":1725751198802},"publisher-location":"Berlin, Heidelberg","reference-count":18,"publisher":"Springer Berlin Heidelberg","isbn-type":[{"type":"print","value":"9783642412172"},{"type":"electronic","value":"9783642412189"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2013]]},"DOI":"10.1007\/978-3-642-41218-9_2","type":"book-chapter","created":{"date-parts":[[2013,10,6]],"date-time":"2013-10-06T21:15:27Z","timestamp":1381094127000},"page":"11-14","source":"Crossref","is-referenced-by-count":2,"title":["Multi-granular Computing in Web Age"],"prefix":"10.1007","author":[{"given":"Bo","family":"Zhang","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ling","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","reference":[{"issue":"15","key":"2_CR1","doi-asserted-by":"publisher","first-page":"6424","DOI":"10.1073\/pnas.0700622104","volume":"104","author":"T. Serre","year":"2007","unstructured":"Serre, T., Oliva, A., Poggio, T.: A feed-forward architecture accounts for rapid categorization. Proc. of the National Academy of Sciences (PNAS)\u00a0104(15), 6424\u20136429 (2007)","journal-title":"Proc. of the National Academy of Sciences (PNAS)"},{"key":"2_CR2","unstructured":"Yao, J., Vasilakos, A.V., Pedryez, W.: Granular computing: perspectives and challenges. will appears in IEEE Trans. on Cybernetics (2012)"},{"key":"2_CR3","unstructured":"Zhang, B., Zhang, L.: Theory and Application of Problem Solving. North-Holland Elsevier Science Publishers B.V. (1992)"},{"key":"2_CR4","unstructured":"Hobbs, J.R.: Granularity. In: Proc. of IJCAI, Los, Angeles, USA, pp. 432\u2013435 (1985)"},{"key":"2_CR5","doi-asserted-by":"crossref","unstructured":"Olshausen, B.: Emergence of simple-sell receptive properties by learning a sparse code for natural image. Nature (1996)","DOI":"10.1038\/381607a0"},{"key":"2_CR6","doi-asserted-by":"crossref","unstructured":"Benjio, Y., Lamblin, P., Popovici, D., Larochelle: Greedy layer-wise training of deep networks. In: Advances in Neural Information Processing Systems (NIPS 2006), vol.\u00a019, pp. 153\u2013160. MIT Press (2007)","DOI":"10.7551\/mitpress\/7503.003.0024"},{"key":"2_CR7","doi-asserted-by":"publisher","first-page":"1527","DOI":"10.1162\/neco.2006.18.7.1527","volume":"18","author":"G.E. Hinton","year":"2006","unstructured":"Hinton, G.E., Osindero, S., Teh, Y.-W.: A fast learning algorithm for deep belief nets. Neural Communication\u00a018, 1527\u20131554 (2006)","journal-title":"Neural Communication"},{"key":"2_CR8","doi-asserted-by":"crossref","unstructured":"Le, Q.V., et al.: Building high level feature using large scale unsupervised learning. In: Proc. 29th ICML, Edinburgh, Scotland, UK (2012)","DOI":"10.1109\/ICASSP.2013.6639343"},{"key":"2_CR9","doi-asserted-by":"crossref","unstructured":"Hu, X., Qi, P., Zhang, B.: Hierarchical K-means algorithm for modeling visual area V2 neurons. In: 19th International Conference on Neural Information Processing, Doha, Qatar, November 12-15 (2012)","DOI":"10.1007\/978-3-642-34487-9_46"},{"issue":"6","key":"2_CR10","doi-asserted-by":"publisher","first-page":"1554","DOI":"10.1214\/aoms\/1177699147","volume":"37","author":"L.E. Baum","year":"1966","unstructured":"Baum, L.E., Petrie, T.: Statistical inference for probabilistic functions of finite state Markov chains. The Annals of Mathematical Statistics\u00a037(6), 1554\u20131563 (1966)","journal-title":"The Annals of Mathematical Statistics"},{"key":"2_CR11","unstructured":"Lafferty, J., et al.: Conditional random fields: probabilistic models for segmenting and labeling sequence data. In: Proc. of International Conference on Machine Learning, ICML (2001)"},{"key":"2_CR12","unstructured":"Taskar, B., et al.: Max-margin Markov networks. In: Advances in Neural Information Processing Systems (INIPS) (2003)"},{"key":"2_CR13","doi-asserted-by":"crossref","unstructured":"Zhu, J., Xing, E., Zhang, B.: Laplace maximum margin Markov networks. In: Proc. of International Conference on Machine Learning (ICML) (2008)","DOI":"10.1145\/1390156.1390314"},{"issue":"6022","key":"2_CR14","doi-asserted-by":"publisher","first-page":"1279","DOI":"10.1126\/science.1192788","volume":"331","author":"J.E. Tenenbaum","year":"2011","unstructured":"Tenenbaum, J.E., et al.: How to grow a mind. Science\u00a0331(6022), 1279\u20131285 (2011)","journal-title":"Science"},{"key":"2_CR15","unstructured":"Xu, M., Zhu, J., Zhang, B.: Bayesian non-parameter max-margin matrix factorization for collaborative prediction. In: Advances in Neural Information Processing Systems, NIPS (2012)"},{"key":"2_CR16","unstructured":"Zhu, J., Chen, N., Perkins, H., Zhang, B.: Gibbs max-margin supervised topic models with fast ampling algorithms. In: ICML (2013)"},{"key":"2_CR17","unstructured":"Xu, M., Zhu, J., Zhang, B.: Fast max-margin matrix factorization with data augmentation. In: ICML (2013)"},{"key":"2_CR18","doi-asserted-by":"crossref","unstructured":"Zhu, J., Zheng, X., Zhou, L., Zhang, B.: Scalable inference in max-margin topic models. In: SIGKDD (2013)","DOI":"10.1145\/2487575.2487658"}],"container-title":["Lecture Notes in Computer Science","Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing"],"original-title":[],"link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-642-41218-9_2","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,7,4]],"date-time":"2023-07-04T22:22:11Z","timestamp":1688509331000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-642-41218-9_2"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2013]]},"ISBN":["9783642412172","9783642412189"],"references-count":18,"URL":"https:\/\/doi.org\/10.1007\/978-3-642-41218-9_2","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2013]]}}}