Literatura académica sobre el tema "Intelligent recommendation system"
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Artículos de revistas sobre el tema "Intelligent recommendation system"
Kathait, ShailendraSingh, Shubhrita Tiwari y PiyushKumar Singh. "INTELLIGENT RECOMMENDATION SYSTEM." International Journal of Advanced Research 5, n.º 2 (28 de febrero de 2017): 1649–56. http://dx.doi.org/10.21474/ijar01/3328.
Texto completoMishra, Ikshita, Ankita Sharma y 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 completoRtili, Mohammed Kamal, Ali Dahmani y 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 completoNaik, 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 completoHirolikar, D. S., Ajinkya Satuse, Omkar Bhalerao, Pavan Pawar y 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 mayo de 2022): 611–22. http://dx.doi.org/10.22214/ijraset.2022.42255.
Texto completoYang, 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., 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 completoCui, Xiaoyue. "An Adaptive Recommendation Algorithm of Intelligent Clothing Design Elements Based on Large Database". Mobile Information Systems 2022 (6 de junio de 2022): 1–10. http://dx.doi.org/10.1155/2022/3334047.
Texto completoMao, Qingqing, Aihua Dong, Qingying Miao y 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 completoChen, Qing Zhang, Yu Jie Pei, Yan Jin y Li Yan Zhang. "Research on Intelligent Recommendation Method and its Application on Internet Bookstore". Advanced Materials Research 121-122 (junio de 2010): 447–52. http://dx.doi.org/10.4028/www.scientific.net/amr.121-122.447.
Texto completoTesis sobre el tema "Intelligent recommendation system"
Thiengburanathum, Pree. "An intelligent destination recommendation system for tourists". Thesis, Bournemouth University, 2018. http://eprints.bournemouth.ac.uk/30571/.
Texto completoXu, Shuting. "Study and Design of an Intelligent Preconditioner Recommendation System". UKnowledge, 2005. http://uknowledge.uky.edu/gradschool_diss/327.
Texto completoZhang, Junjie. "Development of a consumer-oriented intelligent garment recommendation system". Thesis, Lille 1, 2017. http://www.theses.fr/2017LIL10026/document.
Texto completoGarment 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 completoIn 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 completoChi, 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 completoCommercial 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"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 completoLagerqvist, Gustaf y 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 completoSun, 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 completoLibros sobre el tema "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 completoVarlamov, Oleg. Mivar databases and rules. ru: INFRA-M Academic Publishing LLC., 2021. http://dx.doi.org/10.12737/1508665.
Texto completoWilliams, Bradley P. ITS procurement: Analysis and recommendations. Charlottesville, Va: Virginia Transportation Research Council, 1994.
Buscar texto completoAmerica, IVHS. Federal IVHS program recommendations for fiscal years 1994 and 1995. Washington, DC: IVHS America, 1992.
Buscar texto completoservice), SpringerLink (Online, ed. Modeling Intention in Email: Speech Acts, Information Leaks and Recommendation Models. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011.
Buscar texto completoAffairs, 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.
Buscar texto completoEnsuring 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.
Buscar texto completoChe, Natasha X. Intelligent Export Diversification: An Export Recommendation System with Machine Learning. International Monetary Fund, 2020.
Buscar texto completoChe, Natasha X. Intelligent Export Diversification: An Export Recommendation System with Machine Learning. International Monetary Fund, 2020.
Buscar texto completoChe, Natasha X. Intelligent Export Diversification: An Export Recommendation System with Machine Learning. International Monetary Fund, 2020.
Buscar texto completoCapítulos de libros sobre el tema "Intelligent recommendation system"
Padhi, Ashis Kumar, Ayog Mohanty y Sipra Sahoo. "FindMoviez: A Movie Recommendation System". En Intelligent Systems, 49–57. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-33-6081-5_5.
Texto completoFrykowska, Adrianna, Izabela Zbieć, Patryk Kacperski, Peter Vesely y Andrea Studenicova. "Movies Recommendation System". En 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 completoKumar, Keshav, Vatsal Sinha, Aman Sharma, M. Monicashree, M. L. Vandana y B. S. Vijay Krishna. "AI-Assisted College Recommendation System". En Intelligent Sustainable Systems, 141–50. Singapore: Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-2894-9_11.
Texto completoGund, Rohit, James Andro-Vasko, Doina Bein y Wolfgang Bein. "Recommendation System Using MixPMF". En 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 completoChaitra, D., V. R. Badri Prasad y B. N. Vinay. "A Comprehensive Travel Recommendation System". En ICT with Intelligent Applications, 623–31. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-4177-0_62.
Texto completoZhao, Ziyin, Lei Zhou y Tongtong Zhang. "Intelligent Recommendation System for Eyeglass Design". En 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 completoJain, Kartik Narendra, Vikrant Kumar, Praveen Kumar y Tanupriya Choudhury. "Movie Recommendation System: Hybrid Information Filtering System". En 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 completoForestiero, Agostino. "AIRS: Ant-Inspired Recommendation System". En 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 completoLekshmi Priya, T. y Harikumar Sandhya. "Matrix Factorization for Recommendation System". En 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 completoVoggu, Suman Venkata Sai, Yuvraj Singh Champawat, Swaraj Kothari y B. K. Tripathy. "Recommendation System Using Community Identification". En 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 completoActas de conferencias sobre el tema "Intelligent recommendation system"
Toskova, Asya y Georgi Penchev. "Intelligent game recommendation system". En THERMOPHYSICAL BASIS OF ENERGY TECHNOLOGIES (TBET 2020). AIP Publishing, 2021. http://dx.doi.org/10.1063/5.0042063.
Texto completoStan, Cristiana y Irina Mocanu. "An Intelligent Personalized Fashion Recommendation System". En 2019 22nd International Conference on Control Systems and Computer Science (CSCS). IEEE, 2019. http://dx.doi.org/10.1109/cscs.2019.00042.
Texto completoChoi, Chang, Miyoung Cho, Junho Choi, Myunggwon Hwang, Jongan Park y Pankoo Kim. "Travel Ontology for Intelligent Recommendation System". En 2009 Third Asia International Conference on Modelling & Simulation. IEEE, 2009. http://dx.doi.org/10.1109/ams.2009.75.
Texto completoZHANG, J., X. ZENG, L. KOEHL y M. DONG. "CONSUMER-ORIENTED INTELLIGENT GARMENT RECOMMENDATION SYSTEM". En Conference on Uncertainty Modelling in Knowledge Engineering and Decision Making (FLINS 2016). WORLD SCIENTIFIC, 2016. http://dx.doi.org/10.1142/9789813146976_0140.
Texto completoTu, Qingqing y Le Dong. "An Intelligent Personalized Fashion Recommendation System". En 2010 International Conference on Communications, Circuits and Systems (ICCCAS). IEEE, 2010. http://dx.doi.org/10.1109/icccas.2010.5581949.
Texto completoSaxena, Rohan, Maheep Chaudhary, Chandresh Kumar Maurya y Shitala Prasad. "An Intelligent Recommendation-cum-Reminder System". En 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 completoOng, Kyle, Su-Cheng Haw y Kok-Why Ng. "Deep Learning Based-Recommendation System". En 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 completoWong, Tak-Lam. "An intelligent recommendation system using preference regularization". En 2014 14th International Conference on Intelligent Systems Design and Applications (ISDA). IEEE, 2014. http://dx.doi.org/10.1109/isda.2014.7066284.
Texto completoMeehan, Kevin, Tom Lunney, Kevin Curran y Aiden McCaughey. "Context-aware intelligent recommendation system for tourism". En 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 completoUppada, Santosh Kumar, Dani Prakash Esukapalli y B. Sivaselvan. "MitrApp: An Intelligent Recommendation System For Counselling". En 2020 IEEE 4th Conference on Information & Communication Technology (CICT). IEEE, 2020. http://dx.doi.org/10.1109/cict51604.2020.9312107.
Texto completoInformes sobre el tema "Intelligent recommendation system"
Gehlhaus, Diana, Luke Koslosky, Kayla Goode y Claire Perkins. U.S. AI Workforce: Policy Recommendations. Center for Security and Emerging Technology, octubre de 2021. http://dx.doi.org/10.51593/20200087.
Texto completoLegree, Peter J. y 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, marzo de 1991. http://dx.doi.org/10.21236/ada236625.
Texto completoReeb, Tyler D. y Stacey Park. Trade and Transportation Talent Pipeline Blueprints: Building UniversityIndustry Talent Pipelines in Colleges of Continuing and Professional Education. Mineta Transportation Institute, febrero de 2023. http://dx.doi.org/10.31979/mti.2023.2144.
Texto completoPyta, V., Bharti Gupta, Shaun Helman, Neale Kinnear y Nathan Stuttard. Update of INDG382 to include vehicle safety technologies. TRL, julio de 2020. http://dx.doi.org/10.58446/thco7462.
Texto completoBourrier, Mathilde, Michael Deml y Farnaz Mahdavian. Comparative report of the COVID-19 Pandemic Responses in Norway, Sweden, Germany, Switzerland and the United Kingdom. University of Stavanger, noviembre de 2022. http://dx.doi.org/10.31265/usps.254.
Texto completoDaudelin, Francois, Lina Taing, Lucy Chen, Claudia Abreu Lopes, Adeniyi Francis Fagbamigbe y Hamid Mehmood. Mapping WASH-related disease risk: A review of risk concepts and methods. United Nations University Institute for Water, Environment and Health, diciembre de 2021. http://dx.doi.org/10.53328/uxuo4751.
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