Zobrazeno 1 - 10
of 18 477
pro vyhledávání: '"cs.IR"'
Autor:
Bian, Weijie, Wu, Kailun, Ren, Lejian, Pi, Qi, Zhang, Yujing, Xiao, Can, Sheng, Xiang-Rong, Zhu, Yong-Nan, Chan, Zhangming, Mou, Na, Luo, Xinchen, Xiang, Shiming, Zhou, Guorui, Zhu, Xiaoqiang, Deng, Hongbo
Feature interaction has been recognized as an important problem in machine learning, which is also very essential for click-through rate (CTR) prediction tasks. In recent years, Deep Neural Networks (DNNs) can automatically learn implicit nonlinear i
Externí odkaz:
http://arxiv.org/abs/2011.05625
Autor:
Jiang, Biye, Zhang, Pengye, Chen, Rihan, Dai, Binding, Luo, Xinchen, Yang, Yin, Wang, Guan, Zhou, Guorui, Zhu, Xiaoqiang, Gai, Kun
Modern large-scale systems such as recommender system and online advertising system are built upon computation-intensive infrastructure. The typical objective in these applications is to maximize the total revenue, e.g. GMV~(Gross Merchandise Volume)
Externí odkaz:
http://arxiv.org/abs/2006.09684
Autor:
Qi, Pi, Zhu, Xiaoqiang, Zhou, Guorui, Zhang, Yujing, Wang, Zhe, Ren, Lejian, Fan, Ying, Gai, Kun
Rich user behavior data has been proven to be of great value for click-through rate prediction tasks, especially in industrial applications such as recommender systems and online advertising. Both industry and academy have paid much attention to this
Externí odkaz:
http://arxiv.org/abs/2006.05639
Publikováno v:
Information Sciences. 630:325-340
In this study, we deal with the problem of judging the credibility of movie reviews. The problem is challenging because even experts cannot clearly and efficiently judge the credibility of a movie review and the number of movie reviews is very large.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::af776f80bada0403fa85793060eebdbe
https://doi.org/10.1016/j.ins.2023.01.138
https://doi.org/10.1016/j.ins.2023.01.138
Autor:
Jibing Gong, Yao Wan, Ye Liu, Xuewen Li, Yi Zhao, Cheng Wang, Yuting Lin, Xiaohan Fang, Wenzheng Feng, Jingyi Zhang, Jie Tang
Publikováno v:
ACM Transactions on the Web. 17:1-27
Massive open online courses (MOOCs) , which offer open access and widespread interactive participation through the internet, are quickly becoming the preferred method for online and remote learning. Several MOOC platforms offer the service of course
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::390f8bf3c49f2893a32855658a77f8d9
https://doi.org/10.1145/3580510
https://doi.org/10.1145/3580510
Publikováno v:
Natural Language Engineering. :1-31
Latent semantic analysis (LSA) and correspondence analysis (CA) are two techniques that use a singular value decomposition for dimensionality reduction. LSA has been extensively used to obtain low-dimensional representations that capture relationship
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::15c3fea3dcee988721aebe27863c54f2
https://doi.org/10.1017/s1351324923000244
https://doi.org/10.1017/s1351324923000244
Autor:
Kleyko, Denis, Bybee, Connor, Huang, Ping-Chen, Kymn, Christopher J., Olshausen, Bruno A., Frady, E. Paxon, Sommer, Friedrich T.
Publikováno v:
Neural Computation. :1-28
We investigate the task of retrieving information from compositional distributed representations formed by Hyperdimensional Computing/Vector Symbolic Architectures and present novel techniques which achieve new information rate bounds. First, we prov
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f15c68889ea10bf3df7d150c27ff4373
https://doi.org/10.1162/neco_a_01590
https://doi.org/10.1162/neco_a_01590
Publikováno v:
ACM Transactions on Interactive Intelligent Systems. 13:1-36
When people search for information about a new topic within large document collections, they implicitly construct a mental model of the unfamiliar information space to represent what they currently know and guide their exploration into the unknown. B
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6ddce8efcb10af32cb4531454f2fda0d
https://doi.org/10.1145/3588319
https://doi.org/10.1145/3588319
Publikováno v:
ACM Transactions on Information Systems. 41:1-29
The goal of a next basket recommendation (NBR) system is to recommend items for the next basket for a user, based on the sequence of their prior baskets. Recently, a number of methods with complex modules have been proposed that claim state-of-the-ar
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1ba476595b4b3c2dfd74d2c941e8ce2e
https://doi.org/10.1145/3587153
https://doi.org/10.1145/3587153
Autor:
Dugang Liu, Pengxiang Cheng, Zinan Lin, Xiaolian Zhang, Zhenhua Dong, Rui Zhang, Xiuqiang He, Weike Pan, Zhong Ming
Publikováno v:
ACM Transactions on Information Systems. 41:1-26
Debiased recommendation with a randomized dataset has shown very promising results in mitigating the system-induced biases. However, it still lacks more theoretical insights or an ideal optimization objective function compared with the other more wel
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ba382bb6bc8d5e5e829859108d22b1c9
https://doi.org/10.1145/3582002
https://doi.org/10.1145/3582002