460510. Recommender systems
| Title | 460510. Recommender systems |
|---|---|
| Parent | 4605. Data management and data science |
Latest research outputs
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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
Fuzzy and neutrosophic modeling for link prediction in social networks
Tuan, Tran Manh, Chuan, Pham Minh, Ali, Mumtaz, Ngan, Tran Thi, Mittal, Mamta and Son, Le Hoang. 2019. "Fuzzy and neutrosophic modeling for link prediction in social networks." Evolving Systems. 10, pp. 629-634. https://doi.org/10.1007/s12530-018-9251-yArticle
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
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
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
A survey of privacy solutions using blockchain for recommender systems: current status, classification and open issues
Abduljabbar, Tamara Abdulmunim, Tao, Xiaohui, Zhang, Ji, Zhou, Xujuan, Li, Lin and Cai, Yi. 2021. "A survey of privacy solutions using blockchain for recommender systems: current status, classification and open issues." The Computer Journal. 64 (7), pp. 1104-1129. https://doi.org/10.1093/comjnl/bxab065Article
Forecasting long-term precipitation for water resource management: a new multi-step data-intelligent modelling approach
Ali, Mumtaz, Deo, Ravinesh C., Xiang, Yong, Li, Ya and Yaseen, Zaher Mundher. 2020. "Forecasting long-term precipitation for water resource management: a new multi-step data-intelligent modelling approach." Hydrological Sciences Journal. 65 (16), pp. 2693-2708. https://doi.org/10.1080/02626667.2020.1808219Article
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
Event prediction through structural intelligence in online social networks
Tan, Leonard. 2020. Event prediction through structural intelligence in online social networks. PhD Thesis Doctor of Philosophy. University of Southern Queensland. https://doi.org/10.26192/asxq-ax90PhD Thesis
Design and performance of two decomposition paradigms in forecasting daily solar radiation with evolutionary polynomial regression: wavelet transform versus ensemble empirical mode decomposition
Rezaie-Balf, Mohammad, Kim, Sungwon, Ghaemi, Alireza and Deo, Ravinesh. 2021. "Design and performance of two decomposition paradigms in forecasting daily solar radiation with evolutionary polynomial regression: wavelet transform versus ensemble empirical mode decomposition." Deo, Ravinesh, Samui, Pijush and Roy, Sanjiban Sekhar (ed.) Predictive modelling for energy management and power systems engineering. Amsterdam, Netherlands. Elsevier. pp. 115-142Edited book (chapter)
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
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
Near real-time global solar radiation forecasting at multiple time-step horizons using the long short-term memory network
Huynh, Anh Ngoc‐Lan, Deo, Ravinesh C., An-Vo, Duc-Anh, Ali, Mumtaz, Raj, Nawin and Abdulla, Shahab. 2020. "Near real-time global solar radiation forecasting at multiple time-step horizons using the long short-term memory network." Energies. 13 (14). https://doi.org/10.3390/en13143517Article
Adaptive boost LS-SVM classification approach for time-series signal classification in epileptic seizure diagnosis applications
Al-Hadeethi, Hanan, Abdulla, Shahab, Diykh, Mohammed, Deo, Ravinesh C. and Green, Jonathan H.. 2020. "Adaptive boost LS-SVM classification approach for time-series signal classification in epileptic seizure diagnosis applications." Expert Systems with Applications. 161. https://doi.org/10.1016/j.eswa.2020.113676Article
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
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
A novel differential privacy recommendation method based on distributed framework
Zheng, Xiaoyao, Luo, Yonglong, Zhang, Ji, Sun, Liping and Chen, Fulong. 2018. "A novel differential privacy recommendation method based on distributed framework." Tong, Hanghang, Li, Zhenhui (Jessie), Zhu, Feida and Yu, Jeffrey (ed.) 2018 Workshop on Scalable and Applicable Recommendation Systems (SAREC 2018), in conjunction with the 18th IEEE International Conference on Data Mining (ICDM 2018). Singapore 17 - 20 Nov 2018 Los Alamitos, California. https://doi.org/10.1109/ICDMW.2018.00189Paper
Mining health knowledge graph for health risk prediction
Tao, Xiaohui, Pham, Thuan, Zhang, Ji, Yong, Jianming, Goh, Wee Pheng, Zhang, Wenping and Cai, Yi. 2020. "Mining health knowledge graph for health risk prediction." World Wide Web. 23 (4), pp. 2341-2362. https://doi.org/10.1007/s11280-020-00810-1Article
Hybridized neural fuzzy ensembles for dust source modeling and prediction
Rahmati, Omid, Panahi, Mahdi, Ghiasi, Seid Saeid, Deo, Ravinesh C., Tiefenbacher, John P., Pradhan, Biswajeet, Jahani, Ali, Goshtasb, Hamid, Kornejady, Aiding, Shahabi, Himan, Shirzadi, Ataollah, Khosravi, Hassan, Moghaddam, Davoud Davoudi, Mohtashamian, Maryamsadat and Bui, Dieu Tien. 2020. "Hybridized neural fuzzy ensembles for dust source modeling and prediction." Atmospheric Environment. 224, pp. 1-11. https://doi.org/10.1016/j.atmosenv.2020.117320Article
Enhanced deep learning algorithm development to detect pain intensity from facial expression images
Bargshady, Ghazal, Zhou, Xujuan, Deo, Ravinesh C., Soar, Jeffery, Whittaker, Frank and Wang, Hua. 2020. "Enhanced deep learning algorithm development to detect pain intensity from facial expression images." Expert Systems with Applications. 149, pp. 1-10. https://doi.org/10.1016/j.eswa.2020.113305Article
A hybrid air quality early-warning framework: an hourly forecasting model with online sequential extreme learning machines and empirical mode decomposition algorithms
Sharma, Ekta, Deo, Ravinesh C., Prasad, Ramendra and Parisi, Alfio V.. 2020. "A hybrid air quality early-warning framework: an hourly forecasting model with online sequential extreme learning machines and empirical mode decomposition algorithms." Science of the Total Environment. 709, pp. 1-23. https://doi.org/10.1016/j.scitotenv.2019.135934Article
Hybrid particle swarm optimization for rule discovery in the diagnosis of coronary artery disease
Zomorodi-Moghadam, Mariam, Abdar, Moloud, Davarzani, Zohreh, Zhou, Xujuan, Pławiak, Pawel and Acharya, U. Rajendra. 2021. "Hybrid particle swarm optimization for rule discovery in the diagnosis of coronary artery disease." Expert Systems: the journal of knowledge engineering. 38 (1), pp. 1-17. https://doi.org/10.1111/exsy.12485Article
Capability and robustness of novel hybridized models used for drought hazard modeling in southeast Queensland, Australia
Rahmati, Omid, Panahi, Mahdi, Kalantari, Zahra, Soltani, Elinaz, Falah, Fatemeh, Dayal, Kavina S., Mohammadi, Farnoush, Deo, Ravinesh C., Tiefenbacher, John and Bui, Dieu Tien. 2020. "Capability and robustness of novel hybridized models used for drought hazard modeling in southeast Queensland, Australia." Science of the Total Environment. 718, pp. 1-17. https://doi.org/10.1016/j.scitotenv.2019.134656Article
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
Incorporating synoptic-scale climate signals for streamflow modelling over the Mediterranean region using machine learning models
Kisi, Ozgur, Choubin, Bahram, Deo, Ravinesh C. and Yaseen, Zaheer Mundher. 2019. "Incorporating synoptic-scale climate signals for streamflow modelling over the Mediterranean region using machine learning models." Hydrological Sciences Journal. 64 (10), pp. 1240-1252. https://doi.org/10.1080/02626667.2019.1632460Article
Improving SPI-derived drought forecasts incorporating synoptic-scale climate indices in multi-phase multivariate empirical mode decomposition model hybridized with simulated annealing and kernel ridge regression algorithms
Ali, Mumtaz, Deo, Ravinesh C., Maraseni, Tek and Downs, Nathan J.. 2019. "Improving SPI-derived drought forecasts incorporating synoptic-scale climate indices in multi-phase multivariate empirical mode decomposition model hybridized with simulated annealing and kernel ridge regression algorithms." Journal of Hydrology. 576, pp. 164-184. https://doi.org/10.1016/j.jhydrol.2019.06.032Article
Deep Learning Neural Networks Trained with MODIS Satellite-Derived Predictors for Long-Term Global Solar Radiation Prediction
Ghimire, Sujan, Deo, Ravinesh C., Raj, Nawin and Mi, Jianchun. 2019. "Deep Learning Neural Networks Trained with MODIS Satellite-Derived Predictors for Long-Term Global Solar Radiation Prediction." Energies. 12 (12), pp. 1-42. https://doi.org/10.3390/en12122407Article
PMT: new analytical framework for automated evaluation of geo-environmental modelling approaches
Rahmati, Omid, Kornejady, Aiding, Samadi, Mahmood, Deo, Ravinesh C., Conoscenti, Christian, Lombardo, Luigi, Dayal, Kavina, Taghizadeh-Mehrjardi, Ruhollah, Pourghasemi, Hamid Reza, Kumar, Sandeep and Bui, Dieu Tien. 2019. "PMT: new analytical framework for automated evaluation of geo-environmental modelling approaches." Science of the Total Environment. 664, pp. 296-311. https://doi.org/10.1016/j.scitotenv.2019.02.017Article
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
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
Long-term modelling of wind speeds using six different heuristic artificial intelligence approaches
Maroufpoor, Saman, Sanikhani, Hadi, Kisi, Ozgur, Deo, Ravinesh C. and Yaseen, Zaher Mundher. 2019. "Long-term modelling of wind speeds using six different heuristic artificial intelligence approaches." International Journal of Climatology. 39 (8), pp. 3543-3557. https://doi.org/10.1002/joc.6037Article
Development and evaluation of hybrid artificial neural network architectures for modeling spatio-temporal groundwater fluctuations in a complex aquifer system
Roshni, Thendiyath, Jha, Madan K., Deo, Ravinesh C. and Vandana, A.. 2019. "Development and evaluation of hybrid artificial neural network architectures for modeling spatio-temporal groundwater fluctuations in a complex aquifer system." Water Resources Management. 33 (7), pp. 2381-2397. https://doi.org/10.1007/s11269-019-02253-4Article
A novel social network hybrid recommender system based on hypergraph topologic structure
Zheng, Xiaoyao, Luo, Yonglong, Sun, Liping, Ding, Xintao and Zhang, Ji. 2018. "A novel social network hybrid recommender system based on hypergraph topologic structure." World Wide Web. 21 (4), pp. 985-1013. https://doi.org/10.1007/s11280-017-0494-5Article
Logic connectives of complex fuzzy sets
Ngan, Tran Thi, Lan, Luong Thi Hong, Ali, Mumtaz, Tamir, Dan, Son, Le Hoang, Tuan, Tran Manh, Rishe, Naphtali and Kandel, Abe. 2018. "Logic connectives of complex fuzzy sets." Romanian Journal of Information Science and Technology. 21 (4), pp. 344-357.Article
Artificial intelligence approach for the prediction of Robusta coffee yield using soil fertility properties
Kouadio, Louis, Deo, Ravinesh C., Byrareddy, Vivekananda, Adamowski, Jan F., Mushtaq, Shahbaz and Nguyen, Van Phuong. 2018. "Artificial intelligence approach for the prediction of Robusta coffee yield using soil fertility properties." Computers and Electronics in Agriculture. 155, pp. 324-338. https://doi.org/10.1016/j.compag.2018.10.014Article
Multi-stage hybridized online sequential extreme learning machine integrated with Markov Chain Monte Carlo copula-Bat algorithm for rainfall forecasting
Ali, Mumtaz, Deo, Ravinesh C., Downs, Nathan J. and Maraseni, Tek. 2018. "Multi-stage hybridized online sequential extreme learning machine integrated with Markov Chain Monte Carlo copula-Bat algorithm for rainfall forecasting." Atmospheric Research. 213, pp. 450-464. https://doi.org/10.1016/j.atmosres.2018.07.005Article
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
Non-tuned data intelligent model for soil temperature estimation: a new approach
Sanikhani, Hadi, Deo, Ravinesh C., Yaseen, Zaher Mundheer, Eray, Okan and Kisi, Ozgur. 2018. "Non-tuned data intelligent model for soil temperature estimation: a new approach." Geoderma. 330, pp. 52-64. https://doi.org/10.1016/j.geoderma.2018.05.030Article
An ensemble-ANFIS based uncertainty assessment model for forecasting multi-scalar standardized precipitation index
Ali, Mumtaz, Deo, Ravinesh C., Downs, Nathan J. and Maraseni, Tek. 2018. "An ensemble-ANFIS based uncertainty assessment model for forecasting multi-scalar standardized precipitation index." Atmospheric Research. 207, pp. 155-180. https://doi.org/10.1016/j.atmosres.2018.02.024Article
A new approach to predict daily pH in rivers based on the 'a trous' redundant wavelet transform algorithm
Rajaee, Taher, Ravansalar, Masoud, Adamowski, Jan F. and Deo, Ravinesh C.. 2018. "A new approach to predict daily pH in rivers based on the 'a trous' redundant wavelet transform algorithm." Water, Air and Soil Pollution: an international journal of environmental pollution. 229 (3). https://doi.org/10.1007/s11270-018-3715-3Article