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Neural News Recommendation with Topic-Aware News Representation
2019
Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics
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News recommendation can help users find interested news and alleviate information overload. ...
Acknowledgments The authors would like to thank Microsoft News for providing technical support and data in the experiments, and Jiun-Hung Chen (Microsoft News) and Ying Qiao (Microsoft News) for their ...
Conclusion In this paper, we propose a neural news recommendation approach with topic-aware news representations. ...
doi:10.18653/v1/p19-1110
dblp:conf/acl/WuWAHX19
fatcat:zuyjmouzuzc2hpx6a5qxhrpa64
Personalized News Recommendation: Methods and Challenges
[article]
2022
arXiv
pre-print
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2021 pre-print arXiv:2106.08934v2 fatcat:mpbs3vr75ncw7npnp5uhwj5v4eOther Versions
Personalized news recommendation is an important technique to help users find their interested news information and alleviate their information overload. ...
To help researchers master the advances in personalized news recommendation over the past years, in this paper we present a comprehensive overview of personalized news recommendation. ...
TANR [157] uses an auxiliary news topic prediction task to help learn topic-aware news representations. ...
arXiv:2106.08934v3
fatcat:iagqsw73hrehxaxpvpydvtr26m
Personalized News Recommendation: Methods and Challenges
2022
ACM Transactions on Information Systems
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Personalized news recommendation is important for users to find interested news information and alleviate information overload. ...
To help researchers master the advances in personalized news recommendation, in this paper we present a comprehensive overview of personalized news recommendation. ...
TANR [205] uses an auxiliary news topic prediction task to help learn topic-aware news representations. ...
doi:10.1145/3530257
fatcat:xzghh6cut5ahhgxz4mkzgy74ja
Neural News Recommendation with Long- and Short-term User Representations
2019
Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics
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Personalized news recommendation is important to help users find their interested news and improve reading experience. ...
Acknowledgement The authors would like to thank Microsoft News for providing technical support and data in the experiments, and Jiun-Hung Chen (Microsoft News) and Ying Qiao (Microsoft News) for their ...
Wang et al. (2018) proposed to learn the representations of news using knowledge-aware convolutional neural network (CNN), and learn the representations of users from their browsed news based on the similarities ...
doi:10.18653/v1/p19-1033
dblp:conf/acl/AnWWZLX19
fatcat:gj3pkktkvrfung75bvypee3ohi
End-to-End Segmentation-based News Summarization
[article]
2021
arXiv
pre-print
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In this paper, we bring a new way of digesting news content by introducing the task of segmenting a news article into multiple sections and generating the corresponding summary to each section. ...
We make two contributions towards this new task. First, we create and make available a dataset, SegNews, consisting of 27k news articles with sections and aligned heading-style section summaries. ...
Furthermore, we designed a segmentation-aware attention mechanism, which allows neural decoder to capture segmentation information in the source texts. ...
arXiv:2110.07850v1
fatcat:czteuaxppvdbfjyi2lg5kpki4y
Guided Alignment Training for Topic-Aware Neural Machine Translation
[article]
2016
arXiv
pre-print
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With both novel features, the BLEU score of the NMT system on a product title set improves from 18.6 to 21.3%. ...
In this paper, we propose an effective way for biasing the attention mechanism of a sequence-to-sequence neural machine translation (NMT) model towards the well-studied statistical word alignment models ...
the LDA-predicted topic distribution vectors of the same dimension in the readout layer of the neural network deteriorated the BLEU and TER scores significantly. ...
arXiv:1607.01628v1
fatcat:76eb6a5hhzb7xastmois4l4hqe
Neural Networks and Learning Systems for Human Machine Interfacing
2019
Neurocomputing
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The paper titled "Text-based indoor place recognition with deep neural network" presents a new indoor place recognition scheme using deep neural network to improve the recognition framework by utilizing ...
The paper titled "Improved Itracker Combined with Bidirectional Long Short-Term Memory for 3D Gaze Estimation using Appearance Cues" proposes an improved Itracker to predict the subject's gaze for a single ...
doi:10.1016/j.neucom.2019.10.058
fatcat:yz4zj6t72rcezejfixznn2c3p4
Neural News Recommendation with Negative Feedback
[article]
2021
arXiv
pre-print
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In this paper, we propose a neural news recommendation approach which can incorporate the implicit negative user feedback. ...
Besides, we propose an interactive news modeling method to consider the relatedness between title and body in news modeling. ...
Then, we use the title representation as the query of the body attention network to select words in news body according to their relevance to the content of news title, and the output title-aware body ...
arXiv:2101.04328v1
fatcat:oilphr4mrrdghi6ssi67e3d2qa
Neural news recommendation with negative feedback
2020
CCF Transactions on Pervasive Computing and Interaction
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In this paper, we propose a neural news recommendation approach which can incorporate the implicit negative user feedback. ...
Besides, we propose an interactive news modeling method to consider the relatedness between title and body in news modeling. ...
Acknowledgements The authors would like to thank Microsoft News for providing technical support and data. ...
doi:10.1007/s42486-020-00044-0
fatcat:ox4j56jzl5hbvlccnpyzfg6uvu
Sentiment Analysis for Social Media
2019
Applied Sciences
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In the third work, titled "Sentiment-Aware Word Embedding for Emotion Classification" [8] , Mao et al. suggest the use of a sentiment-aware word embedding for improving emotional analysis. ...
Finally, they incorporate the lexicons in a deep neural network-based recommender system to predict the users' online purchasing behaviour. ...
doi:10.3390/app9235037
fatcat:jg4fgxwnqneuhohyuwxmjndzsu
Use of Artificial Intelligence for Predicting COVID-19 Outcomes: A Scoping Review
[chapter]
2022
Studies in Health Technology and Informatics
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The reviewed artificial intelligence methods were able to predict cases, death, mortality, and severity. AI tools can serve as powerful means for building predictive analytics during pandemics. ...
The highest accuracy rate was 98% on the three days mortality prediction using the time-aware long short-term memory neural network. ...
This topic was relatively narrow. In the future study, we will design a method to measure model performance and also extend our topics to other predictors that could be predicted by AI. ...
doi:10.3233/shti210923
pmid:35062156
fatcat:22zzveimprafbkkvscnna2tzxm
Neural News Recommendation with Collaborative News Encoding and Structural User Encoding
[article]
2021
arXiv
pre-print
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Existing works typically encode news title and content separately while neglecting their semantic interaction, which is inadequate for news text comprehension. ...
CNE equipped with bidirectional LSTMs encodes news title and content collaboratively with cross-selection and cross-attention modules to learn semantic-interactive news representations. ...
This reveals the challenge of predicting a user's news-clicking behavior when her browsing history covers too many kinds of news topics. ...
arXiv:2109.00750v2
fatcat:t6c3g65jpbdzvmfmi7nhjwdgpe
Editorial: Anticipatory Systems: Humans Meet Artificial Intelligence
2021
Frontiers in Psychology
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Of course, there are many interesting studies in this topic, which invites the discussion of a new computing paradigm, "Anticipatory Computing." ...
In the paper titled "A Meaning-Aware Cultural Tourism Intelligent Navigation System Based on Anticipatory Calculation" by Meng and Liu utilizes the theory of desired behavior to obtain the relation between ...
doi:10.3389/fpsyg.2021.721879
fatcat:sqdwprqxt5ethnuslifr3zp6j4
DKN: Deep Knowledge-Aware Network for News Recommendation
[article]
2018
arXiv
pre-print
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The key component of DKN is a multi-channel and word-entity-aligned knowledge-aware convolutional neural network (KCNN) that fuses semantic-level and knowledge-level representations of news. ...
DKN is a content-based deep recommendation framework for click-through rate prediction. ...
The user's embedding and the candidate news' embedding are finally processed by a deep neural network (DNN) for CTR prediction. ...
arXiv:1801.08284v2
fatcat:c6p7njibivfsricpgrxin2nj2u
Analysis and Applications of Location-Aware Big Complex Network Data
2019
Complexity
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The paper titled "Targeted Influential Nodes Selection in Location-aware Social Networks" by S. ...
The papers titled "Sign Prediction on Unlabeled Social Networks Using Branch and Bound Optimized Transfer Learning" by W. ...
doi:10.1155/2019/3410262
fatcat:klkq3sed5fby3cfycdbth57rba
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