Zobrazeno 1 - 10
of 11
pro vyhledávání: '"Elvis Saravia"'
Autor:
Elvis Saravia, 艾維斯
103
Today, most personalized and recommendation services are built around user interest extraction models but the outputs of these algorithms are ambiguous in nature. This makes it inherently difficult to understand what users are personally int
Today, most personalized and recommendation services are built around user interest extraction models but the outputs of these algorithms are ambiguous in nature. This makes it inherently difficult to understand what users are personally int
Externí odkaz:
http://ndltd.ncl.edu.tw/handle/85487346306925810242
Publikováno v:
EMNLP
Emotions are expressed in nuanced ways, which varies by collective or individual experiences, knowledge, and beliefs. Therefore, to understand emotion, as conveyed through text, a robust mechanism capable of capturing and modeling different linguisti
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::356de230d681ab9befc410cb97d256b2
https://doi.org/10.18653/v1/d18-1404
https://doi.org/10.18653/v1/d18-1404
Publikováno v:
TAAI
Recently, several news aggregation services have emerged to deal with the problem of information overload and news personalization. These news providers are able to organize news based on content similarity as a strategy to improve the user reading e
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::fbc8a52a7b9326b51752d868bd7a3fa3
https://doi.org/10.1109/taai.2017.37
https://doi.org/10.1109/taai.2017.37
Publikováno v:
ASONAM
The rapid growth of social networks have enabled users to instantly share what is happening around them. With the character-limitation and other feature constraints imposed by microblogs, users are obliged to express their intentions in implicit form
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::970f6bd8ead2d21c6d260bbf08a3f938
https://doi.org/10.1145/3110025.3120987
https://doi.org/10.1145/3110025.3120987
Publikováno v:
Social Network Analysis and Mining. 6
The connected society we live in today has allowed online users to willingly share opinions on an unprecedented scale. Motivated by the advent of mass opinion sharing, it is then crucial to devise algorithms that efficiently identify the emotions exp
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2ec1ed7737762040ff6f27d418cdd653
https://doi.org/10.1007/s13278-016-0403-4
https://doi.org/10.1007/s13278-016-0403-4
Publikováno v:
2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5f93cdb66dc22e9ec6d731527139f53b
https://doi.org/10.1109/asonam.2016.7752434
https://doi.org/10.1109/asonam.2016.7752434
Publikováno v:
2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f6e8525d11d4e2b206a37a8310106805
https://doi.org/10.1109/asonam.2016.7752261
https://doi.org/10.1109/asonam.2016.7752261
Publikováno v:
ASONAM
Today, most personalized and recommendation services are built around interest extraction models but the outputs of these algorithms are ambiguous in nature. This makes it difficult to understand what users are personally interested in and more impor
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::33d790ce894a1f002322ab5ebfa4dd92
https://doi.org/10.1145/2808797.2808916
https://doi.org/10.1145/2808797.2808916
Publikováno v:
ASONAM
Opinionated user-generated content has been increasingly flooding the internet since the rise of the Web 2.0. Many of this content is generated by the occurrence of different events varying in time, scale and location. In recent years there has been
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b301451d065b0ea2744931070dab6021
https://doi.org/10.1145/2808797.2808801
https://doi.org/10.1145/2808797.2808801
Publikováno v:
ASONAM
Traditional classifiers require extracting high dimensional feature representations, which become computationally expensive to process and can misrepresent or deteriorate the accuracy of a classifier. By utilizing a more representative list of extrac
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::bfd58b04d225bc7b45b62eeef983c929
https://doi.org/10.1145/2808797.2809419
https://doi.org/10.1145/2808797.2809419