Zobrazeno 1 - 8
of 8
pro vyhledávání: '"Siamak Faridani"'
Autor:
Siamak Faridani, Kurt Gramoll
Publikováno v:
2008 Annual Conference & Exposition Proceedings.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b1d738d7c0ee7241b312bfade1172f96
https://doi.org/10.18260/1-2--4190
https://doi.org/10.18260/1-2--4190
Publikováno v:
IEEE Transactions on Human-Machine Systems, vol 45, iss 1
Goldberg, K; Faridani, S; & Alterovitz, R. (2015). Two large open-access datasets for fitts' law of human motion and a succinct derivation of the square-root variant. IEEE Transactions on Human-Machine Systems, 45(1). doi: 10.1109/THMS.2014.2360281. UC Berkeley: Retrieved from: http://www.escholarship.org/uc/item/3t4049ss
Goldberg, K; Faridani, S; & Alterovitz, R. (2015). Two large open-access datasets for fitts' law of human motion and a succinct derivation of the square-root variant. IEEE Transactions on Human-Machine Systems, 45(1). doi: 10.1109/THMS.2014.2360281. UC Berkeley: Retrieved from: http://www.escholarship.org/uc/item/3t4049ss
© 2014 IEEE. Fitts' law specifies a logarithmic relationship between motion duration and the ratio of target distance over target size. This paper introduces two large open-access datasets from experimental user studies: first a controlled (in-lab)
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a3e5be6dabaf1fe6a55c050e83d743a5
https://doi.org/10.1109/thms.2014.2360281
https://doi.org/10.1109/thms.2014.2360281
Publikováno v:
IFAC Proceedings Volumes. 42:56-61
The scientific field study of wildlife often requires vigilant observation of detailed animal behavior over extended periods. In remote and inhospitable locations, observation can be an arduous, expensive, and dangerous experience for field scientist
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e2ddfee87ea37fc7cbee5216f923cf14
https://doi.org/10.3182/20091006-3-us-4006.00010
https://doi.org/10.3182/20091006-3-us-4006.00010
Autor:
Siamak Faridani
Publikováno v:
RecSys
Standard Sentiment Analysis applies Natural Language Processing methods to assess an "approval" value of a given text, categorizing it into "negative", "neutral", or "positive" or on a linear scale. Sentiment Analysis can be used to infer ratings val
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c3e784c0c336c9f15e2ddb2123b2b138
https://doi.org/10.1145/2043932.2044005
https://doi.org/10.1145/2043932.2044005
Publikováno v:
CHI Extended Abstracts
Most online discussion interfaces organize textual responses using linear lists. Such lists do not scale to the number of responses and cannot convey the diversity of the participants who have contributed. The Opinion Space system is designed to addr
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7ccd7ba5ca41400af5a3d1145341d456
https://doi.org/10.1145/1979742.1979793
https://doi.org/10.1145/1979742.1979793
Publikováno v:
CHI
Internet users are increasingly inclined to contribute comments to online news articles, videos, product reviews, and blogs. The most common interface for comments is a list, sorted by time of entry or by binary ratings. It is widely recognized that
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::eb0f8591262fedddad3ad29c2424bf47
https://doi.org/10.1145/1753326.1753502
https://doi.org/10.1145/1753326.1753502
Publikováno v:
Proceedings of the AAAI Conference on Human Computation and Crowdsourcing. 1:20-21
We propose an iterative approach for inferring a ground truth value of an item from judgments collected form on-line workers. The method is specifically designed for cases in which the collected labels are ordinal. Our algorithm works by iteratively
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b9fd941befeb53552cbbb632d5eb5bd4
https://doi.org/10.1609/hcomp.v1i1.13133
https://doi.org/10.1609/hcomp.v1i1.13133
Autor:
Siamak Faridani, Georg Buscher
Publikováno v:
Proceedings of the AAAI Conference on Human Computation and Crowdsourcing. 1:18-19
We introduce LabelBoost, an ensemble model that utilizes various label aggregation algorithms to build a higher precision algorithm. We compare this algorithm with majority vote, GLAD and an Expectation Maximization model on a publicly available data
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::82b2e7e38fe36f464f6aedcb0220a179
https://doi.org/10.1609/hcomp.v1i1.13134
https://doi.org/10.1609/hcomp.v1i1.13134