Zobrazeno 1 - 10
of 585
pro vyhledávání: '"Piccardi, M."'
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.
Given a large unlabeled document collection, the aim of this paper is to develop an accurate and efficient algorithm for solving the clustering problem over this collection. Document collections typically contain tens or hundreds of thousands of docu
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od_______363::7b6c87e7607107225918385ec55dfc7a
https://hdl.handle.net/10453/170765
https://hdl.handle.net/10453/170765
Autor:
Seifollahi, S, Piccardi, M
Extracting meaningful features from documents can prove critical for a variety of tasks such as classification, clustering and semantic analysis. However, traditional approaches to document feature extraction mainly rely on first-order word statistic
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od_______363::6871f1d5acdb5f33c7a4429c11a97a3c
https://hdl.handle.net/10453/170766
https://hdl.handle.net/10453/170766
Publikováno v:
Revista Veterinaria; 2023, Vol. 34 Issue 2, p76-80, 5p
Publikováno v:
In Theriogenology 15 March 2013 79(5):760-765
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.
Autor:
Gentiluomo, M. Piccardi M., Bertoncini, S., Costello, E., Morelli, L., Landi, S., Milanetto, A. C., Schöttker, B., Di Franco, G., Ermini, S., Scarpa, A., Izbicki, J., Pezzilli, R., Uzunoglu, F., Talar-Wojnarowska, R., Goetz, M., Lawlor, R., Aoki, M., Bueno-de-Mesquita, B., Busch, O., Chammas, R., Tavano, F., van Laarhoven, H., Cavestro, G., Stocker, H., Bazzocchi, F., Pasquali, C., Chen, X., Puzzono, M., Ponz de Leon Pisani, R., Brenner, H., Vodickova, L., Sperti, C., Lovecek, L., Erőss, B., Basso, D., Kupcinskas, J., Vanagas, T., Janciauskas, D., Poskiene, L., Tacelli, M., Mohelnikova Duchonova, B., Capurso, G., Perri, F., Latiano, A., Mambrini, A., Maiello, E., Hegyi, P., Szentesi, A., Bunduc, S., Hussein, T., Arcidiacono, P., Boggi, U., Hackert, T., Archibugi, L., Soucek, P., Vanella, G., Lucchesi, M., Ginocchi, L., Gazouli, M., Zerbi, A., Roth, S., Jamroziak, K., Carrara, S., Hlavac, V., Oliverius, M., Neoptolemos, J., Theodoropoulos, G., van Eijck, C., Dannemann, M., Canzian, F., Tofanelli, S., Campa, D.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::015a6b7f432c10698508d897d146779c
http://hdl.handle.net/11577/3457169
http://hdl.handle.net/11577/3457169
In recent years, neural machine translation (NMT) has achieved unprecedented performance in automated translation of resource-rich languages. However, it has not yet managed to achieve a comparable performance over the many low-resource languages and
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od_______363::ba32e4776fb9f1bee5ebf6a6a1e5f581
https://hdl.handle.net/10453/169528
https://hdl.handle.net/10453/169528
Citation recommendation is a task that aims to automatically select suitable references for a working manuscript. This task has become increasingly urgent as the typical pools of candidates continue to grow, in the order of tens or hundreds of thousa
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od_______363::6d868823329d95e05531e569dd6d52c9
https://hdl.handle.net/10453/155776
https://hdl.handle.net/10453/155776