Zobrazeno 1 - 10
of 19
pro vyhledávání: '"Shahpar Yakhchi"'
Autor:
Seyed Mohssen Ghafari, Amin Beheshti, Aditya Joshi, Cecile Paris, Adnan Mahmood, Shahpar Yakhchi, Mehmet A. Orgun
Publikováno v:
IEEE Access, Vol 8, Pp 144292-144309 (2020)
Level of Trust can determine which source of information is reliable and with whom we should share or from whom we should accept information. There are several applications for measuring trust in Online Social Networks (OSNs), including social spamme
Externí odkaz:
https://doaj.org/article/f9be1204e3b343a7b278eb10726195b2
Publikováno v:
IEEE Access, Vol 8, Pp 178073-178084 (2020)
With the availability of a large amount of user-generated online data, discovering users’ sequential behaviour has become an integral part of a Sequential Recommender System (SRS). Combining the recent observed items (i.e., short-term preferences)
Externí odkaz:
https://doaj.org/article/bc345c01fd104ab9a600b5f62d2d80b9
Autor:
Amin Beheshti, Shahpar Yakhchi, Salman Mousaeirad, Seyed Mohssen Ghafari, Srinivasa Reddy Goluguri, Mohammad Amin Edrisi
Publikováno v:
Algorithms, Vol 13, Iss 8, p 176 (2020)
Intelligence is the ability to learn from experience and use domain experts’ knowledge to adapt to new situations. In this context, an intelligent Recommender System should be able to learn from domain experts’ knowledge and experience, as it is
Externí odkaz:
https://doaj.org/article/93cc5f3e0ca64a8fadfde9cd3abbfdcd
Autor:
Seyed Mohssen Ghafari, Cecile Paris, Amin Beheshti, Alireza Jolfaei, Aditya Joshi, Shahpar Yakhchi, Quan Z. Sheng, Mehmet A. Orgun
Publikováno v:
journal of Data Intelligence. 2:401-417
Trust among users in online social networks is a key factor in determining the amount of information that is perceived as reliable. Compared to the number of users in online social networks, user-specified trust relations are very sparse. This makes
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7e18506cf0550916590d0820525a5491
https://doi.org/10.26421/jdi2.4-1
https://doi.org/10.26421/jdi2.4-1
Publikováno v:
IEEE Access, Vol 8, Pp 178073-178084 (2020)
With the availability of a large amount of user-generated online data, discovering users’ sequential behaviour has become an integral part of a Sequential Recommender System (SRS). Combining the recent observed items (i.e., short-term preferences)
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::10f19232ac3e1fc62cc4383ca04caa1e
https://doi.org/10.1109/access.2020.3004656
https://doi.org/10.1109/access.2020.3004656
Autor:
Aditya Joshi, Cecile Paris, Shahpar Yakhchi, Adnan Mahmood, Seyed Mohssen Ghafari, Mehmet A. Orgun, Amin Beheshti
Publikováno v:
IEEE Access, Vol 8, Pp 144292-144309 (2020)
Level of Trust can determine which source of information is reliable and with whom we should share or from whom we should accept information. There are several applications for measuring trust in Online Social Networks (OSNs), including social spamme
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::cd0de7a536b09b9d66495c887c9002bc
https://ieeexplore.ieee.org/document/9142365/
https://ieeexplore.ieee.org/document/9142365/
Publikováno v:
Service-Oriented Computing – ICSOC 2020 Workshops ISBN: 9783030763510
ICSOC Workshops
ICSOC Workshops
Recommender systems (RSs) have been adopted in a variety set of web services to provide a list of items which a user may interact with in near future. Collaborative filtering (CF) is one of the most widely used mechanism in RSs that focuses on prefer
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::10bbce99497475bd4b05c7dc568d1e87
https://doi.org/10.1007/978-3-030-76352-7_30
https://doi.org/10.1007/978-3-030-76352-7_30
Autor:
Seyed Mohssen Ghafari, Mehmet A. Orgun, Amin Beheshti, Alireza Jolfaei, Cecile Paris, Aditya Joshi, Shahpar Yakhchi
Publikováno v:
MoMM
Trust can be employed for finding reliable information in Online Social Networks (OSNs). Since users in OSNs may intentionally change their behavior over time (in some cases for deceiving other users), modeling (pair-wise) trust relations in such com
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::71e7cb1599c2ea4ad7d4b52b6fd2159f
https://doi.org/10.1145/3428690.3429167
https://doi.org/10.1145/3428690.3429167
Autor:
Mohammad Amin Edrisi, Shahpar Yakhchi, Amin Beheshti, Srinivasa Reddy Goluguri, Seyed Mohssen Ghafari, Salman Mousaeirad
Publikováno v:
Algorithms
Volume 13
Issue 8
Algorithms, Vol 13, Iss 176, p 176 (2020)
Volume 13
Issue 8
Algorithms, Vol 13, Iss 176, p 176 (2020)
Intelligence is the ability to learn from experience and use domain experts&rsquo
knowledge to adapt to new situations. In this context, an intelligent Recommender System should be able to learn from domain experts&rsquo
knowledge and exper
knowledge to adapt to new situations. In this context, an intelligent Recommender System should be able to learn from domain experts&rsquo
knowledge and exper
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ebb80caa85ecd62e495ebff62ef28e3e
Autor:
Amin Beheshti, Vahid Moraveji-Hashemi, Hamid Reza Motahari-Nezhad, Seyed Mohssen Ghafari, Jian Yang, Shahpar Yakhchi
Publikováno v:
WSDM
Enabling the analysis of behavioral disorders over time in social networks, can help in suicide prevention, (school) bullying detection and extremist/criminal activity prediction. In this paper, we present a novel data analytics pipeline to enable th
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6e5bf3e941549c7c339055f8facd73c5
https://doi.org/10.1145/3336191.3371865
https://doi.org/10.1145/3336191.3371865