460510. Recommender systems
| Title | 460510. Recommender systems |
|---|---|
| Parent | 4605. Data management and data science |
Latest research outputs
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Probabilistic and artificial intelligence modelling of drought and agricultural crop yield in Pakistan
Ali, Mumtaz. 2019. Probabilistic and artificial intelligence modelling of drought and agricultural crop yield in Pakistan. PhD Thesis Doctor of Philosophy. University of Southern Queensland. https://doi.org/10.26192/S847-M467PhD Thesis
Random forest predictive model development with uncertainty analysis capability for the estimation of evapotranspiration in an arid oasis region
Wu, Min, Feng, Qi, Wen, Xiaohu, Deo, Ravinesh C., Yin, Zhenliang, Yang, Linshan and Sheng, Danrui. 2020. "Random forest predictive model development with uncertainty analysis capability for the estimation of evapotranspiration in an arid oasis region." Hydrology Research: an international journal. 51 (4), pp. 648-665. https://doi.org/10.2166/nh.2020.012Article
Regional hydrology heterogeneity and the response to climate and land surface changes in arid alpine basin, northwest China
Yang, Linshan, Feng, Qi, Yin, Zhenliang, Deo, Ravinesh C., Wen, Xiaohu, Si, Jianhua and Liu, Wen. 2020. "Regional hydrology heterogeneity and the response to climate and land surface changes in arid alpine basin, northwest China." Catena. 187. https://doi.org/10.1016/j.catena.2019.104345Article
Semantic Knowledge Discovery for User Profiling for Location-Based Recommender Systems
Tao, Xiaohui, Sharma, Nischal, Delaney, Patrick and Hu, Aimin. 2021. "Semantic Knowledge Discovery for User Profiling for Location-Based Recommender Systems." Human-centric Computing and Information Sciences. 1 (1-2), pp. 32-42. https://doi.org/10.2991/hcis.k.210704.001Article
Sentiment Analysis of Chinese E-commerce Reviews Based on BERT
Xie, Song, Cao, Jingjing, Wu, Zhou, Liu, Kai, Tao, Xiaohui and Xie, Haoran. 2021. "Sentiment Analysis of Chinese E-commerce Reviews Based on BERT." 18th IEEE International Conference on Industrial Informatics (INDIN 2020). Warwick, United Kingdom 21 - 23 Jul 2020 Piscataway, United States. https://doi.org/10.1109/INDIN45582.2020.9442190Paper
Short-term electricity demand forecasting with MARS, SVR and ARIMA models using aggregated demand data in Queensland, Australia
Al-Musaylh, Mohanad S., Deo, Ravinesh C., Adamowski, Jan F. and Li, Yan. 2018. "Short-term electricity demand forecasting with MARS, SVR and ARIMA models using aggregated demand data in Queensland, Australia." Advanced Engineering Informatics: the science of supporting knowledge-intensive activities. 35 (C), pp. 1-16. https://doi.org/10.1016/j.aei.2017.11.002Article
Soil moisture forecasting by a hybrid machine learning technique: ELM integrated with ensemble empirical mode decomposition
Prasad, Ramendra, Deo, Ravinesh C., Li, Yan and Maraseni, Tek. 2018. "Soil moisture forecasting by a hybrid machine learning technique: ELM integrated with ensemble empirical mode decomposition." Geoderma. 330, pp. 136-161. https://doi.org/10.1016/j.geoderma.2018.05.035Article
Spatial mapping of short-term solar radiation prediction incorporating geostationary satellite images coupled with deep convolutional LSTM networks for South Korea
Yeom, Jong-Min, Deo, Ravinesh C., Adamowski, Jan F., Park, Seonyoung and Lee, Chang-Suk. 2020. "Spatial mapping of short-term solar radiation prediction incorporating geostationary satellite images coupled with deep convolutional LSTM networks for South Korea." Environmental Research Letters. 15 (9), pp. 1-10. https://doi.org/10.1088/1748-9326/ab9467Article
Synthetic retrieval of hourly net ecosystem exchange using the neural network model with combined MI and GOCI geostationary sensor datasets and ground-based measurements
Yeom, Jong-Min, Deo, Ravinesh, Chun, Junghwa, Hong, Jinkyu, Kim, Dong-Su, Han, Kyung-Soo and Cho, Jaeil. 2017. "Synthetic retrieval of hourly net ecosystem exchange using the neural network model with combined MI and GOCI geostationary sensor datasets and ground-based measurements." International Journal of Remote Sensing. 38 (23), pp. 7441-7456. https://doi.org/10.1080/01431161.2017.1375573Article
The 1st International Workshop on Context-Aware Recommendation Systems with Big Data Analytics (CARS-BDA)
Zhou, Xiangmin, Zhang, Ji and Zhang, Yanchun. 2019. "The 1st International Workshop on Context-Aware Recommendation Systems with Big Data Analytics (CARS-BDA)." 12th ACM International Conference on Web Search and Data Mining (WSDM 2019). Melbourne, Australia 11 - 15 Feb 2019 New York, United States. https://doi.org/10.1145/3289600.3291372Paper
The influence of climatic inputs on stream-flow pattern forecasting: case study of Upper Senegal River
Diop, Lamine, Bodian, Ansoumana, Djaman, Koffi, Yaseen, Zaher Mundher, Deo, Ravinesh C., El-Shafie, Ahmed and Brown, Larry C.. 2018. "The influence of climatic inputs on stream-flow pattern forecasting: case study of Upper Senegal River." Environmental Earth Sciences. 77 (5). https://doi.org/10.1007/s1266Article
The Influence of Consumers' Trust and Cognitive Absorption on Behavioural Intentions to Reuse Recommender Systems
Acharya, Nirmal. 2022. The Influence of Consumers' Trust and Cognitive Absorption on Behavioural Intentions to Reuse Recommender Systems. PhD by Publication Doctor of Philosophy. University of Southern Queensland. https://doi.org/10.26192/q7q92PhD by Publication
The modeling of human facial pain intensity based on Temporal Convolutional Networks trained with video frames in HSV color space
Bargshady, Ghazal, Zhou, Xujuan, Deo, Ravinesh C., Soar, Jeffrey, Whittaker, Frank and Wang, Hua. 2020. "The modeling of human facial pain intensity based on Temporal Convolutional Networks trained with video frames in HSV color space." Applied Soft Computing. 97 (Part A), pp. 1-14. https://doi.org/10.1016/j.asoc.2020.106805Article
Two-phase extreme learning machines integrated with the complete ensemble empirical mode decomposition with adaptive noise algorithm for multi-scale runoff prediction problems
Wen, Xiaohu, Feng, Qi, Deo, Ravinesh C., Wu, Min, Yin, Zhenliang, Yang, Linshan and Singh, Vijay P.. 2019. "Two-phase extreme learning machines integrated with the complete ensemble empirical mode decomposition with adaptive noise algorithm for multi-scale runoff prediction problems." Journal of Hydrology. 570, pp. 167-184. https://doi.org/10.1016/j.jhydrol.2018.12.060Article
Two-phase particle swarm optimized-support vector regression hybrid model integrated with improved empirical mode decomposition with adaptive noise for multiple-horizon electricity demand forecasting
Al-Musaylh, Mohanad S., Deo, Ravinesh C., Li, Yan and Adamowski, Jan F.. 2018. "Two-phase particle swarm optimized-support vector regression hybrid model integrated with improved empirical mode decomposition with adaptive noise for multiple-horizon electricity demand forecasting." Applied Energy. 217, pp. 422-439. https://doi.org/10.1016/j.apenergy.2018.02.140Article
Universally deployable extreme learning machines integrated with remotely sensed MODIS satellite predictors over Australia to forecast global solar radiation: a new approach
Deo, Ravinesh C., Sahin, Mehmet, Adamowski, Jan F. and Mi, Jianchun. 2019. "Universally deployable extreme learning machines integrated with remotely sensed MODIS satellite predictors over Australia to forecast global solar radiation: a new approach." Renewable and Sustainable Energy Reviews. 104, pp. 235-261. https://doi.org/10.1016/j.rser.2019.01.009Article
Using association rules to make rule-based classifiers robust
Hu, Hong and Li, Jiuyong. 2005. "Using association rules to make rule-based classifiers robust." Williams, Hugh E. and Dobbie, Gillian (ed.) ADC 2005: 16th Australasian Database Conference. Newcastle, Australia 31 Jan - 03 Feb 2005 Sydney, Australia.Paper