Zobrazeno 1 - 10
of 85
pro vyhledávání: '"Janez Brank"'
Publikováno v:
Heritage Science, Vol 10, Iss 1, Pp 1-14 (2022)
Abstract The cultural heritage domain in general and silk textiles, in particular, are characterized by large, rich and heterogeneous data sets. Silk heritage vocabulary comes from multiple sources that have been mixed up across time and space. This
Externí odkaz:
https://doaj.org/article/41ff3e189a864724813b195d0ee8cca3
Autor:
M. Besher Massri, Inna Novalija, Dunja Mladenić, Janez Brank, Sara Graça da Silva, Natasza Marrouch, Carla Murteira, Ali Hürriyetoğlu, Beno Šircelj
Publikováno v:
Multimodal Technologies and Interaction, Vol 6, Iss 7, p 57 (2022)
This paper presents an Artificial Intelligence approach to mining context and emotions related to olfactory cultural heritage narratives, particularly to fairy tales. We provide an overview of the role of smell and emotions in literature, as well as
Externí odkaz:
https://doaj.org/article/7757a63db5164f27a4a2015d18139a1d
Publikováno v:
Informatica. 46
Autor:
Stefano Menini, Teresa Paccosi, Sara Tonelli, Marieke Van Erp, Inger Leemans, Pasquale Lisena, Raphael Troncy, William Tullett, Ali Hürriyetoğlu, Ger Dijkstra, Femke Gordijn, Elias Jürgens, Josephine Koopman, Aron Ouwerkerk, Sanne Steen, Inna Novalija, Janez Brank, Dunja Mladenic, Anja Zidar
Publikováno v:
STARTPAGE=1;ENDPAGE=10;TITLE=3rd International Workshop on Computational Approaches to Historical Language Change, LChange 2022
We present a benchmark in six European languages containing manually annotated information about olfactory situations and events following a FrameNet-like approach. The documents selection covers ten domains of interest to cultural historians in the
Publikováno v:
Encyclopedia of Machine Learning and Data Mining ISBN: 9781489975027
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5748b17e373d0a56620c6d2d161308cf
https://doi.org/10.1007/978-1-4899-7687-1_903
https://doi.org/10.1007/978-1-4899-7687-1_903
Publikováno v:
Encyclopedia of Machine Learning and Data Mining ISBN: 9781489975027
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b91546c34392a23c6d0f570ef5114107
https://doi.org/10.1007/978-1-4899-7687-1_75
https://doi.org/10.1007/978-1-4899-7687-1_75
Publikováno v:
Encyclopedia of Machine Learning and Data Mining ISBN: 9781489975027
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5e080bfc88f03be5f3f573eda92abf5c
https://doi.org/10.1007/978-1-4899-7687-1_100
https://doi.org/10.1007/978-1-4899-7687-1_100
Publikováno v:
WWW (Companion Volume)
Event Registry is a system that can analyze news articles and identify in them mentioned world events. The system is able to identify groups of articles that describe the same event. It can identify groups of articles in different languages that desc
Autor:
Jure Leskovec, Janez Brank
Publikováno v:
ACM SIGKDD Explorations Newsletter. 5:160-162
This paper describes our work on the Download Estimation task for KDD Cup 2003. The task requires us to estimate how many times a paper has been downloaded in the first 60 days after it has been published on arXiv.org , a preprint server for papers o
Autor:
Geoffrey I. Webb, Johannes Fürnkranz, Geoffrey Hinton, Claude Sammut, Joerg Sander, Michail Vlachos, Yee Whye Teh, Ying Yang, Dunja Mladeni, Janez Brank, Marko Grobelnik, Ying Zhao, George Karypis, Susan Craw, Martin L. Puterman, Jonathan Patrick
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f1a8c4fead407137448f8f768aaba7c8
https://doi.org/10.1007/978-0-387-30164-8_237
https://doi.org/10.1007/978-0-387-30164-8_237