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Assignors: APPELMAN, BARRY Publication of US20050076241A1 publication Critical patent/US20050076241A1/en Assigned to BANK OF AMERICAN, N.A. ASSIGNMENT OF ASSIGNORS INTEREST (SEE DOCUMENT FOR DETAILS). Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.) Filing date Publication date Priority to US45927203P priority Critical Application filed by America Online Inc filed Critical America Online Inc Priority to US10/746,232 priority patent/US7949759B2/en Priority claimed from PCT/US2003/041499 external-priority patent/WO2004061611A2/en Assigned to AMERICA ONLINE, INC. Original Assignee America Online Inc Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.) ( en Inventor Barry Appelman Current Assignee (The listed assignees may be inaccurate.
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X DEGREES OF SEPARATION PDF
Google Patents Degrees of separation for handling communicationsĭownload PDF Info Publication number US20050076241A1 US20050076241A1 US10/746,232 US74623203A US2005076241A1 US 20050076241 A1 US20050076241 A1 US 20050076241A1 US 74623203 A US74623203 A US 74623203A US 2005076241 A1 US2005076241 A1 US 2005076241A1 Authority US United States Prior art keywords communication intended recipient sender contact list linked Prior art date Legal status (The legal status is an assumption and is not a legal conclusion.
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Google Patents US20050076241A1 - Degrees of separation for handling communications DAD’s Alexander Martos called this phenomenon “re-socialising of arts via natural language processing” or rather “re-a-socialising” since it uncovers asocial societal tendencies and (re-?) introduces them to the world of fine arts.US20050076241A1 - Degrees of separation for handling communications This is of course a direct result of the biases inherent to the word embedding model. As can be seen above, the most similar keywords to “Homosexuality” are “Rape”, “Religion”, “Violence” and “Islam” (all translated from German). OFAI´s Brigitte Krenn found it interesting how the very reglemented and almost scientific language in Belvedere’s keywords (stemming from the Iconclass project) is contrasted with everyday language via usage of word embedding. The word embedding model has been trained on the Wikipedia and Common Crawl corpus, which helps explaining the replication of very common and persisting prejudice in our society. In the above query with the word “Homosexuality” the most similar word out of 22 million terms in the word embedding model is “Paedophilia”, one of the worst prejudice against homosexual people. In the ensuing discussion of results it was found remarkable how machine learning via word embedding replicates existing biases and prejudice in the society. In fourth position is an etching with the only keyword ‘Vulture’, which is semantically close to ‘Angel’, ‘Air’ and ‘Death’ of the ending artwork. The second artwork in the pathway is a relief showing ‘Christ’, while the third is a painting tagged with ‘Death’ and ‘Skeleton’, hence already semantically closer to the topics of ‘Martyrdom’, ‘Suffering’ and ‘Death’ of the end artwork. The above exemplary result starts with a sculpture with keywords ‘Resurrection’ and ‘Christ’ where the painting in the end position has keywords around the topic of ‘Death’ and ‘Martyrdom’. All images by Belvedere, Vienna, Austria ( CC BY-SA 4.0). This is used to embed keywords of Belvedere´s online fine arts collection and obtain pathways through the resulting semantic space. Therefore he used word embedding, which encodes semantic similarities between words by modelling the context to their neighboring words in a large training text corpus. In his work, Arthur Flexer is more interested in finding pathways of the semantic meaning of works of art rather than just their visual features. The presented work is inspired by the project ‘ X Degrees of Separation‘ by ‘Google Arts and Culture’, which explores the “hidden paths through culture” by analyzing visual features of artworks to find pathways between any two artifacts through a chain of artworks. DAD´s Arthur Flexer gave a semi-virtual lecture on “Discovering X Degrees of Keyword Separation in a Fine Arts Collection” at the Austrian Research Institute for Artificial Intelligence ( OFAI, ).