Literatura científica selecionada sobre o tema "Intelligent recommendation system"
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Artigos de revistas sobre o assunto "Intelligent recommendation system"
Kathait, ShailendraSingh, Shubhrita Tiwari e PiyushKumar Singh. "INTELLIGENT RECOMMENDATION SYSTEM." International Journal of Advanced Research 5, n.º 2 (28 de fevereiro de 2017): 1649–56. http://dx.doi.org/10.21474/ijar01/3328.
Texto completo da fonteMishra, Ikshita, Ankita Sharma e Tanuj Deria. "Intelligent Tourist Recommendation System". IJARCCE 6, n.º 4 (30 de abril de 2017): 384–91. http://dx.doi.org/10.17148/ijarcce.2017.6474.
Texto completo da fonteRtili, Mohammed Kamal, Ali Dahmani e Mohamed Khaldi. "Recommendation System Based on the Learners' Tracks in an Intelligent Tutoring System". Journal of Advances in Computer Networks 2, n.º 1 (2014): 40–43. http://dx.doi.org/10.7763/jacn.2014.v2.79.
Texto completo da fonteNaik, Pratiksha Ashok. "Intelligent Food Recommendation System Using Machine Learning". Volume 5 - 2020, Issue 8 - August 5, n.º 8 (27 de agosto de 2020): 616–19. http://dx.doi.org/10.38124/ijisrt20aug414.
Texto completo da fonteHirolikar, D. S., Ajinkya Satuse, Omkar Bhalerao, Pavan Pawar e Hrithik Thorat. "Intelligent Movie Recommendation System Using AI and ML". International Journal for Research in Applied Science and Engineering Technology 10, n.º 5 (31 de maio de 2022): 611–22. http://dx.doi.org/10.22214/ijraset.2022.42255.
Texto completo da fonteYang, Fan. "A hybrid recommendation algorithm–based intelligent business recommendation system". Journal of Discrete Mathematical Sciences and Cryptography 21, n.º 6 (18 de agosto de 2018): 1317–22. http://dx.doi.org/10.1080/09720529.2018.1526408.
Texto completo da fonte., Jay Borade. "INTELLIGENT AGENT FOR TOURISM RECOMMENDATION SYSTEM". International Journal of Research in Engineering and Technology 07, n.º 04 (25 de abril de 2018): 39–46. http://dx.doi.org/10.15623/ijret.2018.0704007.
Texto completo da fonteCui, Xiaoyue. "An Adaptive Recommendation Algorithm of Intelligent Clothing Design Elements Based on Large Database". Mobile Information Systems 2022 (6 de junho de 2022): 1–10. http://dx.doi.org/10.1155/2022/3334047.
Texto completo da fonteMao, Qingqing, Aihua Dong, Qingying Miao e Lu Pan. "Intelligent Costume Recommendation System Based on Expert System". Journal of Shanghai Jiaotong University (Science) 23, n.º 2 (abril de 2018): 227–34. http://dx.doi.org/10.1007/s12204-018-1933-x.
Texto completo da fonteChen, Qing Zhang, Yu Jie Pei, Yan Jin e Li Yan Zhang. "Research on Intelligent Recommendation Method and its Application on Internet Bookstore". Advanced Materials Research 121-122 (junho de 2010): 447–52. http://dx.doi.org/10.4028/www.scientific.net/amr.121-122.447.
Texto completo da fonteTeses / dissertações sobre o assunto "Intelligent recommendation system"
Thiengburanathum, Pree. "An intelligent destination recommendation system for tourists". Thesis, Bournemouth University, 2018. http://eprints.bournemouth.ac.uk/30571/.
Texto completo da fonteXu, Shuting. "Study and Design of an Intelligent Preconditioner Recommendation System". UKnowledge, 2005. http://uknowledge.uky.edu/gradschool_diss/327.
Texto completo da fonteZhang, Junjie. "Development of a consumer-oriented intelligent garment recommendation system". Thesis, Lille 1, 2017. http://www.theses.fr/2017LIL10026/document.
Texto completo da fonteGarment purchasing through the Internet has become an important trend for consumers of all parts of the world. However, in various garment e-shopping systems, it systematically lacks personalized recommendations, like sales advisors in classical shops, in order to propose the most relevant products to different consumers according to their body shapes and fashion requirements. In this thesis, we propose a consumer-oriented recommendation system, which can be used inside a garment online shopping system like a virtual sales advisor. This system has been developed by integrating the professional knowledge of designers and shoppers and taking into account consumers’ perception on products. Following the shopping knowledge on garments, the proposed system recommends garment products to specific consumers by successively executing three modules, namely 1) the Successful Cases Database Module; 2) the Market Forecasting Module; 3) the Knowledge-based Recommendation Module. Also, another module, called the Knowledge Updating Module.This thesis presents an original method for predicting one or several relevant product profiles from a specific consumer profile. It can effectively help consumers to choose garments from the Internet. Compared with other prediction methods, the proposed method is more robust and interpretable owing to its capacity of treating uncertainty
Dong, Min. "Development of an intelligent recommendation system to garment designers for designing new personalized products". Thesis, Lille 1, 2017. http://www.theses.fr/2017LIL10025/document.
Texto completo da fonteIn my PhD research project, we originally propose a Designer-oriented Intelligent Recommendation System (DIRS) for supporting the design of new personalized garment products. For developing this system, we first identify the key components of a garment design process, and then set up a number of relevant databases, from which each design scheme can be formed. Second, we acquire the anthropometric data and designer’s perception on body shapes by using a 3D body scanning system and a sensory evaluation procedure. Third, an instrumental experiment is conducted for measuring the technical parameters of fabrics, and five sensory experiments are carried out in order to acquire designers’ knowledge. The acquired data are used to classify body shapes and model the relations between human bodies and the design factors. From these models, we set up an ontology-based design knowledge base. This knowledge base can be updated by dynamically learning from new design cases. On this basis, we put forward the knowledge-based recommendation system. This system is used with a newly developed design process. This process can be performed repeatedly until the designer’s satisfaction. The proposed recommendation system has been validated through a number of successful real design cases
Lohi, Abdolkhalil. "Investigation of an intelligent personalised service recommendation system in an IMS based cellular mobile network". Thesis, University of Westminster, 2013. https://westminsterresearch.westminster.ac.uk/item/99060/investigation-of-an-intelligent-personalised-service-recommendation-system-in-an-ims-based-cellular-mobile-network.
Texto completo da fonteChi, Cheng. "Personalized pattern recommendation system of men’s shirts based on precise body measurement". Electronic Thesis or Diss., Centrale Lille Institut, 2022. http://www.theses.fr/2022CLIL0003.
Texto completo da fonteCommercial garment recommendation systems have been widely used in the apparel industry. However, existing research on digital garment design has focused on the technical development of the virtual design process, with little knowledge of traditional designers. The fit of a garment plays a significant role in whether a customer purchases that garment. In order to develop a well-fitting garment, designers and pattern makers should adjust the garment pattern several times until the customer is satisfied. Currently, there are three main disadvantages of traditional pattern-making: 1) it is very time-consuming and inefficient, 2) it relies too much on experienced designers, 3) the relationship between the human body shape and the garment is not fully explored. In practice, the designer plays a key role in a successful design process. There is a need to integrate the designer's knowledge and experience into current garment CAD systems to provide a feasible human-centered, low-cost design solution quickly for each personalized requirement. Also, data-based services such as recommendation systems, body shape classification, 3D body modelling, and garment fit assessment should be integrated into the apparel CAD system to improve the efficiency of the design process.Based on the above issues, in this thesis, a fit-oriented garment pattern intelligent recommendation system is proposed for supporting the design of personalized garment products. The system works in combination with a newly developed design process, i.e. body shape identification - design solution recommendation - 3D virtual presentation and evaluation - design parameter adjustment. This process can be repeated until the user is satisfied. The proposed recommendation system has been validated by some successful practical design cases
Robles, Sebastian. "Business intelligence in Chile, recommendations to develop local applications". Thesis, Massachusetts Institute of Technology, 2010. http://hdl.handle.net/1721.1/70831.
Texto completo da fonte"February 2010." Cataloged from PDF version of thesis.
Includes bibliographical references (p. 60).
The volume of information generated from enterprise applications is growing exponentially, and the cost of storage is decreasing rapidly. In addition, cloud-based applications, mobile devices and social networks are becoming relevant sources of unstructured data that provide essential information for strategic decisions making. Therefore, with time, enterprise databases will become more valuable for business but also much harder to integrate, process and analyze. Business Intelligence software was instrumental in helping organizations to analyze information and provide reports to support business decision-making. Accordingly, BI applications evolved as enterprise information grew, hardware-processing capacities developed, and storage cost is being reduced significantly. In this paper, we will analyze the current BI world market and compare it with the Chilean market, in order to come up with business plan recommendations for local developers and systems integrators interested in capitalizing the opportunities generated by the global BI software market consolidation.
by Sebastian Robles.
S.M.in Engineering and Management
Schröder, Anna Marie. "Unboxing The Algorithm : Understandability And Algorithmic Experience In Intelligent Music Recommendation Systems". Thesis, Malmö universitet, Institutionen för konst, kultur och kommunikation (K3), 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:mau:diva-43841.
Texto completo da fonteLagerqvist, Gustaf, e Anton Stålhandske. "Recommendation systems for recruitment within an educational context". Thesis, Malmö universitet, Fakulteten för teknik och samhälle (TS), 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:mau:diva-42902.
Texto completo da fonteSun, Runpu. "Using Social Media Intelligence to Support Business Knowledge Discovery and Decision Making". Diss., The University of Arizona, 2011. http://hdl.handle.net/10150/145394.
Texto completo da fonteLivros sobre o assunto "Intelligent recommendation system"
Varlamov, Oleg. Fundamentals of creating MIVAR expert systems. ru: INFRA-M Academic Publishing LLC., 2021. http://dx.doi.org/10.12737/1513119.
Texto completo da fonteVarlamov, Oleg. Mivar databases and rules. ru: INFRA-M Academic Publishing LLC., 2021. http://dx.doi.org/10.12737/1508665.
Texto completo da fonteWilliams, Bradley P. ITS procurement: Analysis and recommendations. Charlottesville, Va: Virginia Transportation Research Council, 1994.
Encontre o texto completo da fonteAmerica, IVHS. Federal IVHS program recommendations for fiscal years 1994 and 1995. Washington, DC: IVHS America, 1992.
Encontre o texto completo da fonteservice), SpringerLink (Online, ed. Modeling Intention in Email: Speech Acts, Information Leaks and Recommendation Models. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011.
Encontre o texto completo da fonteAffairs, United States Congress Senate Committee on Homeland Security and Governmental. Ensuring full implementation of the 9/11 Commission's recommendations: Hearing before the Committee on Homeland Security and Governmental Affairs, United States Senate, One Hundred Tenth Congress, first session, January 7, 2007. Washington: U.S. G.P.O., 2009.
Encontre o texto completo da fonteEnsuring full implementation of the 9/11 Commission's recommendations: Hearing before the Committee on Homeland Security and Governmental Affairs, United States Senate, One Hundred Tenth Congress, first session, January 7, 2007. Washington: U.S. G.P.O., 2009.
Encontre o texto completo da fonteChe, Natasha X. Intelligent Export Diversification: An Export Recommendation System with Machine Learning. International Monetary Fund, 2020.
Encontre o texto completo da fonteChe, Natasha X. Intelligent Export Diversification: An Export Recommendation System with Machine Learning. International Monetary Fund, 2020.
Encontre o texto completo da fonteChe, Natasha X. Intelligent Export Diversification: An Export Recommendation System with Machine Learning. International Monetary Fund, 2020.
Encontre o texto completo da fonteCapítulos de livros sobre o assunto "Intelligent recommendation system"
Padhi, Ashis Kumar, Ayog Mohanty e Sipra Sahoo. "FindMoviez: A Movie Recommendation System". In Intelligent Systems, 49–57. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-33-6081-5_5.
Texto completo da fonteFrykowska, Adrianna, Izabela Zbieć, Patryk Kacperski, Peter Vesely e Andrea Studenicova. "Movies Recommendation System". In Advances in Intelligent Networking and Collaborative Systems, 579–85. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-29035-1_56.
Texto completo da fonteKumar, Keshav, Vatsal Sinha, Aman Sharma, M. Monicashree, M. L. Vandana e B. S. Vijay Krishna. "AI-Assisted College Recommendation System". In Intelligent Sustainable Systems, 141–50. Singapore: Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-2894-9_11.
Texto completo da fonteGund, Rohit, James Andro-Vasko, Doina Bein e Wolfgang Bein. "Recommendation System Using MixPMF". In Advances in Intelligent Systems and Computing, 263–68. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-97652-1_32.
Texto completo da fonteChaitra, D., V. R. Badri Prasad e B. N. Vinay. "A Comprehensive Travel Recommendation System". In ICT with Intelligent Applications, 623–31. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-4177-0_62.
Texto completo da fonteZhao, Ziyin, Lei Zhou e Tongtong Zhang. "Intelligent Recommendation System for Eyeglass Design". In Advances in Intelligent Systems and Computing, 402–11. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-20441-9_42.
Texto completo da fonteJain, Kartik Narendra, Vikrant Kumar, Praveen Kumar e Tanupriya Choudhury. "Movie Recommendation System: Hybrid Information Filtering System". In Intelligent Computing and Information and Communication, 677–86. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-10-7245-1_66.
Texto completo da fonteForestiero, Agostino. "AIRS: Ant-Inspired Recommendation System". In Advances in Intelligent Systems and Computing, 213–24. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-11310-4_19.
Texto completo da fonteLekshmi Priya, T., e Harikumar Sandhya. "Matrix Factorization for Recommendation System". In Advances in Intelligent Systems and Computing, 267–80. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-3514-7_22.
Texto completo da fonteVoggu, Suman Venkata Sai, Yuvraj Singh Champawat, Swaraj Kothari e B. K. Tripathy. "Recommendation System Using Community Identification". In Advances in Intelligent Systems and Computing, 125–32. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-1286-5_11.
Texto completo da fonteTrabalhos de conferências sobre o assunto "Intelligent recommendation system"
Toskova, Asya, e Georgi Penchev. "Intelligent game recommendation system". In THERMOPHYSICAL BASIS OF ENERGY TECHNOLOGIES (TBET 2020). AIP Publishing, 2021. http://dx.doi.org/10.1063/5.0042063.
Texto completo da fonteStan, Cristiana, e Irina Mocanu. "An Intelligent Personalized Fashion Recommendation System". In 2019 22nd International Conference on Control Systems and Computer Science (CSCS). IEEE, 2019. http://dx.doi.org/10.1109/cscs.2019.00042.
Texto completo da fonteChoi, Chang, Miyoung Cho, Junho Choi, Myunggwon Hwang, Jongan Park e Pankoo Kim. "Travel Ontology for Intelligent Recommendation System". In 2009 Third Asia International Conference on Modelling & Simulation. IEEE, 2009. http://dx.doi.org/10.1109/ams.2009.75.
Texto completo da fonteZHANG, J., X. ZENG, L. KOEHL e M. DONG. "CONSUMER-ORIENTED INTELLIGENT GARMENT RECOMMENDATION SYSTEM". In Conference on Uncertainty Modelling in Knowledge Engineering and Decision Making (FLINS 2016). WORLD SCIENTIFIC, 2016. http://dx.doi.org/10.1142/9789813146976_0140.
Texto completo da fonteTu, Qingqing, e Le Dong. "An Intelligent Personalized Fashion Recommendation System". In 2010 International Conference on Communications, Circuits and Systems (ICCCAS). IEEE, 2010. http://dx.doi.org/10.1109/icccas.2010.5581949.
Texto completo da fonteSaxena, Rohan, Maheep Chaudhary, Chandresh Kumar Maurya e Shitala Prasad. "An Intelligent Recommendation-cum-Reminder System". In CODS-COMAD 2022: 5th Joint International Conference on Data Science & Management of Data (9th ACM IKDD CODS and 27th COMAD). New York, NY, USA: ACM, 2022. http://dx.doi.org/10.1145/3493700.3493724.
Texto completo da fonteOng, Kyle, Su-Cheng Haw e Kok-Why Ng. "Deep Learning Based-Recommendation System". In CIIS 2019: 2019 The 2nd International Conference on Computational Intelligence and Intelligent Systems. New York, NY, USA: ACM, 2019. http://dx.doi.org/10.1145/3372422.3372444.
Texto completo da fonteWong, Tak-Lam. "An intelligent recommendation system using preference regularization". In 2014 14th International Conference on Intelligent Systems Design and Applications (ISDA). IEEE, 2014. http://dx.doi.org/10.1109/isda.2014.7066284.
Texto completo da fonteMeehan, Kevin, Tom Lunney, Kevin Curran e Aiden McCaughey. "Context-aware intelligent recommendation system for tourism". In 2013 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops 2013). IEEE, 2013. http://dx.doi.org/10.1109/percomw.2013.6529508.
Texto completo da fonteUppada, Santosh Kumar, Dani Prakash Esukapalli e B. Sivaselvan. "MitrApp: An Intelligent Recommendation System For Counselling". In 2020 IEEE 4th Conference on Information & Communication Technology (CICT). IEEE, 2020. http://dx.doi.org/10.1109/cict51604.2020.9312107.
Texto completo da fonteRelatórios de organizações sobre o assunto "Intelligent recommendation system"
Gehlhaus, Diana, Luke Koslosky, Kayla Goode e Claire Perkins. U.S. AI Workforce: Policy Recommendations. Center for Security and Emerging Technology, outubro de 2021. http://dx.doi.org/10.51593/20200087.
Texto completo da fonteLegree, Peter J., e Philip D. Gillis. A Review of and Recommendations for Procedures Used to Evaluate the External Effectiveness of Intelligent Tutoring Systems. Fort Belvoir, VA: Defense Technical Information Center, março de 1991. http://dx.doi.org/10.21236/ada236625.
Texto completo da fonteReeb, Tyler D., e Stacey Park. Trade and Transportation Talent Pipeline Blueprints: Building UniversityIndustry Talent Pipelines in Colleges of Continuing and Professional Education. Mineta Transportation Institute, fevereiro de 2023. http://dx.doi.org/10.31979/mti.2023.2144.
Texto completo da fontePyta, V., Bharti Gupta, Shaun Helman, Neale Kinnear e Nathan Stuttard. Update of INDG382 to include vehicle safety technologies. TRL, julho de 2020. http://dx.doi.org/10.58446/thco7462.
Texto completo da fonteBourrier, Mathilde, Michael Deml e Farnaz Mahdavian. Comparative report of the COVID-19 Pandemic Responses in Norway, Sweden, Germany, Switzerland and the United Kingdom. University of Stavanger, novembro de 2022. http://dx.doi.org/10.31265/usps.254.
Texto completo da fonteDaudelin, Francois, Lina Taing, Lucy Chen, Claudia Abreu Lopes, Adeniyi Francis Fagbamigbe e Hamid Mehmood. Mapping WASH-related disease risk: A review of risk concepts and methods. United Nations University Institute for Water, Environment and Health, dezembro de 2021. http://dx.doi.org/10.53328/uxuo4751.
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