Zobrazeno 1 - 10
of 12
pro vyhledávání: '"Tara Safavi"'
Publikováno v:
Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1b6ac3d2e5fdadbe6bf131776ce6af71
https://doi.org/10.1145/3534678.3542913
https://doi.org/10.1145/3534678.3542913
Publikováno v:
ACM SIGIR Forum. 54:1-9
We report on the First Workshop on Bias in Automatic Knowledge Graph Construction (KG-BIAS), which was co-located with the Automated Knowledge Base Construction (AKBC) 2020 conference. Identifying and possibly remediating any sort of bias in knowledg
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a560d9587152d200b81a387cc5aa60e2
https://doi.org/10.1145/3483382.3483393
https://doi.org/10.1145/3483382.3483393
Publikováno v:
Knowledge and Information Systems. 61:987-1017
Discovering and analyzing networks from non-network data is a task with applications in fields as diverse as neuroscience, genomics, climate science, economics, and more. In domains where networks are discovered on multiple time series, the most comm
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::fae8a47d8ffc1b503697a2dfd0e1257e
https://doi.org/10.1007/s10115-018-1293-8
https://doi.org/10.1007/s10115-018-1293-8
Publikováno v:
EMNLP (1)
Little is known about the trustworthiness of predictions made by knowledge graph embedding (KGE) models. In this paper we take initial steps toward this direction by investigating the calibration of KGE models, or the extent to which they output conf
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8791232fbdda287d6068b5b16b751f14
http://arxiv.org/abs/2004.01168
http://arxiv.org/abs/2004.01168
Autor:
Ned B. Friend, Shane Williams, Tara Safavi, Marcin Juraszek, Paul N. Bennett, Robert Sim, Adam Fourney, Danai Koutra
Publikováno v:
WSDM
Individuals' personal information collections (their emails, files, appointments, web searches, contacts, etc) offer a wealth of insights into the organization and structure of their everyday lives. In this paper we address the task of learning repre
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c1edfb96aede494e4383cc9131f1dbfd
https://doi.org/10.1145/3336191.3371828
https://doi.org/10.1145/3336191.3371828
Autor:
Danai Koutra, Tara Safavi
Publikováno v:
EMNLP (1)
We present CoDEx, a set of knowledge graph completion datasets extracted from Wikidata and Wikipedia that improve upon existing knowledge graph completion benchmarks in scope and level of difficulty. In terms of scope, CoDEx comprises three knowledge
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::93dd993b2fd3f0534ed729e02fa7588a
Publikováno v:
ICDM
Graph classification is an important problem in many fields, from bioinformatics and neuroscience to computer vision and social network analysis. That said, the task of comparing graphs for the purpose of graph classification faces several major chal
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::736aace8262c6322d87d2d8f3743c37d
https://doi.org/10.1109/icdm.2019.00039
https://doi.org/10.1109/icdm.2019.00039
Publikováno v:
ICDM
Safavi, T, Belth, C, Faber, L, Mottin, D, Müller, E & Koutra, D 2019, ' Personalized Knowledge Graph Summarization: From the Cloud to Your Pocket ', Paper presented at IEEE International Conference on Data Mining, Beijing, China, 08/11/2019-11/11/2019 . < https://web.eecs.umich.edu/~dkoutra/papers/19_ICDM_GLIMPSE-CR.pdf >
Safavi, T, Belth, C, Faber, L, Mottin, D, Müller, E & Koutra, D 2019, ' Personalized Knowledge Graph Summarization: From the Cloud to Your Pocket ', Paper presented at IEEE International Conference on Data Mining, Beijing, China, 08/11/2019-11/11/2019 . < https://web.eecs.umich.edu/~dkoutra/papers/19_ICDM_GLIMPSE-CR.pdf >
The increasing scale of encyclopedic knowledge graphs (KGs) calls for summarization as a way to help users efficiently access and distill world knowledge. Motivated by the disparity between individuals' limited information needs and the massive scale
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6f524cdd17477509f3ee8634aab92990
https://doi.org/10.1109/icdm.2019.00063
https://doi.org/10.1109/icdm.2019.00063
Publikováno v:
KDD
From artificial intelligence to network security to hardware design, it is well-known that computing research drives many important technological and societal advancements. However, less is known about the long-term career paths of the people behind
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0dda9c76f97027fd79bf3f5228639728
http://arxiv.org/abs/1805.06534
http://arxiv.org/abs/1805.06534
Publikováno v:
Social Network Analysis and Mining. 8
Summarizing a large graph with a much smaller graph is critical for applications like speeding up intensive graph algorithms and interactive visualization. In this paper, we propose CONditional Diversified Network Summarization (CondeNSe), a Minimum
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::25b06d320aed386a4135354acb9577ae
https://doi.org/10.1007/s13278-018-0491-4
https://doi.org/10.1007/s13278-018-0491-4