Gotowe bibliografie tematyczne / RECOMMENDATION TECHNIQUES

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Gotowa bibliografia na temat „RECOMMENDATION TECHNIQUES”

Autor: Grafiati

Data publikacji: 11 września 2023

Data aktualizacji: 26 lipca 2025

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Artykuły w czasopismach na temat "RECOMMENDATION TECHNIQUES"

Dondekar, Anupama D., and Balwant A. Sonkamble. "Tag Recommendation Techniques for Images: A Survey." International Journal of Signal Processing Systems 5, no. 4 (2017): 116–22. http://dx.doi.org/10.18178/ijsps.5.4.116-122.

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Gorli, Ravi, and Bagusetty Ajay Ram. "MRML-Movie Recommendation Model with Machine Learning Techniques." International Journal of Science and Research (IJSR) 12, no. 5 (2023): 298–302. http://dx.doi.org/10.21275/sr23322101301.

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Tewari, Anand Shanker, and Asim Gopal Barman. "Sequencing of items in personalized recommendations using multiple recommendation techniques." Expert Systems with Applications 97 (May 2018): 70–82. http://dx.doi.org/10.1016/j.eswa.2017.12.019.

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TR, Mahesh, and V Vinoth Kumar. "Clustering Techniques for Recommendation of Movies." International Journal of Data Informatics and Intelligent Computing 1, no. 2 (2022): 16–22. http://dx.doi.org/10.59461/ijdiic.v1i2.17.

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A recommendation system employs a variety of algorithms to provide users with recommendations of any kind. The most well-known technique, collaborative filtering, involves users with similar preferences although it is not always as effective when dealing with large amounts of data. Improvements to this approach are required as the dataset size increases. Here, in our suggested method, we combine a hierarchical clustering methodology with a collaborative filtering algorithm for making recommendations. Additionally, the Principle Component Analysis (PCA) method is used to condense the dimensions

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El-Deeb, Reham Hesham, Walid Abdelmoez, and Nashwa El-Bendary. "Enhancing E-Recruitment Recommendations Through Text Summarization Techniques." Information 16, no. 4 (2025): 333. https://doi.org/10.3390/info16040333.

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This research aims to enhance e-recruitment systems using text summarization techniques and pretrained large language models (LLMs). A job recommender system is built with integrated text summarization. The text summarization techniques that are selected are BART, T5 (Text-to-Text Transfer Transformer), BERT, and Pegasus. Content-based recommendation is the model chosen to be implemented. The LinkedIn Job Postings dataset is used. The evaluation of the text summarization techniques is performed using ROUGE-1, ROUGE-2, and ROUGE-L. The results of this approach deduce that the recommendation doe

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Idakwo, John, Joshua Babatunde Agbogun, and Taiwo Kolajo. "A Survey on Recommendation System Techniques." UMYU Scientifica 2, no. 2 (2023): 112–19. http://dx.doi.org/10.56919/usci.2322.012.

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The primary objective of recommender systems (RS) is to analyze user behavior and propose relevant items or services that users would find appealing. Recommender systems have gained significant prominence in various domains such as information technology and e-commerce. They achieve this by customizing recommendations based on individual preferences, efficiently filtering options from a vast pool, and enabling users to discover content that matches their interests. Numerous recommendation techniques have been developed to generate personalized suggestions, including collaborative filtering, co

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Al-Absi, Mohammed Abdulhakim, and Hind R’bigui. "Process Discovery Techniques Recommendation Framework." Electronics 12, no. 14 (2023): 3108. http://dx.doi.org/10.3390/electronics12143108.

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In a competitive environment, organizations need to continuously understand, analyze and improve the behavior of processes to maintain their position in the market. Process mining is a set of techniques that allows organizations to have an X-ray view of their processes by extracting process related knowledge from the information recorded in today’s process aware information systems such as ‘Enterprise Resource Planning’ systems, ‘Business Process Management’ systems, ‘Supply Chain Management’ systems, etc. One of the major categories of process mining techniques is the process of discovery. Th

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Gaurkhede, Miss Pratiksha P. "Review Paper on various Recommendation Techniques of Friends Recommendation System." International Journal for Research in Applied Science and Engineering Technology 9, no. 4 (2021): 894–97. http://dx.doi.org/10.22214/ijraset.2021.33770.

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Chandrasekaran, K. S., G. A. Varun, D. S. Sujjit, H. Subashree, and R. Thirumaalchelvan. "Movie Recommendation System Using Machine Learning Techniques." International Journal of Multidisciplinary Research Transactions 5, no. 7 (2023): 148–57. https://doi.org/10.5281/zenodo.7942135.

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Movie recommendation systems are becoming increasingly popular, with many businesses looking to leverage the power of data to personalize the user experience and improve customer engagement. Machine learning techniques are an effective way to analyse large datasets of user behavior and generate accurate and relevant recommendations. In this project, we propose a machine learning-based movie recommendation system that uses content-based filtering techniques to generate personalized recommendations for users. Our system takes into account the user's viewing history, ratings, and preferences,

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P, Bhagya Sri, Sindhu Sri G, Jaya Sri K, Leela Poojitha V, and Sajida Sultana Sk. "Intelligent book recommendation system using ML techniques." ITM Web of Conferences 74 (2025): 03007. https://doi.org/10.1051/itmconf/20257403007.

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The current research focuses on a recommendation system based on Decision Tree, Naive Bayes, Ridge Classifier, and Random Forest, using a new hybrid method combining Singular Value Decomposition (SVD) and K-Nearest Neighbors (KNN). The Decision Tree model reaches a good trade-off for precision, recall, and F1 metrics, acting as a benchmark. On the other hand, the hybrid model greatly surpasses the remaining ones in such a way that precision is as high as 89.35%, recall is 59.01%, and F1 is up to 71.30%, thus reinforcing the notion that it finds user preferences for recommendations more effecti

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Rozprawy doktorskie na temat "RECOMMENDATION TECHNIQUES"

Martins, Diogo Marques. "Trajectory clustering techniques with application to route recommendation." Master's thesis, Universidade de Aveiro, 2015. http://hdl.handle.net/10773/18581.

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Mestrado em Engenharia de Computadores e Telemática<br>O uso generalizado de dispositivos capazes de obter e transmitir dados sobre a localização de objetos ao longo do tempo tem permitido recolher grandes volumes de dados espácio-temporais. Por isso, tem-se assistido a uma procura crescente de técnicas e ferramentas para a análise de grandes volumes de dados espácio-temporais com o intuito de disponibilizar uma gama variada de serviços baseados na localização. Esta dissertação centra-se no desenvolvimento de um sistema para recomendaSr trajetos com base em dados históricos sobre a localizaçã

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Vahabi, Hossein. "Recommendation techniques for Web search and social media." Thesis, IMT Alti Studi Lucca, 2012. http://e-theses.imtlucca.it/86/1/Vahabi_phdthesis.pdf.

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Recommenders aim to solve the information and interaction overload. A recommender system is a tool that identifies highly relevant items of interest for a user. In this thesis we aim to harness the information available through Web to build recommender systems. In particularwe study on a number of different recommendation problems: "correct tag recommendation", "query recommendation", "tweet recommendation", and "tourist points of interest recommendation". For each problem, we describe and evaluate effective solutions using novel efficient techniques.

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Alabdulrahman, Rabaa. "Towards Personalized Recommendation Systems: Domain-Driven Machine Learning Techniques and Frameworks." Thesis, Université d'Ottawa / University of Ottawa, 2020. http://hdl.handle.net/10393/41012.

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Recommendation systems have been widely utilized in e-commerce settings to aid users through their shopping experiences. The principal advantage of these systems is their ability to narrow down the purchase options in addition to marketing items to customers. However, a number of challenges remain, notably those related to obtaining a clearer understanding of users, their profiles, and their preferences in terms of purchased items. Specifically, recommender systems based on collaborative filtering recommend items that have been rated by other users with preferences similar to those of the targ

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Aleksandra, Klašnja-Milićević. "Personalized Recommendation Based on Collaborative Tagging Techniques for an e‐Learning System." Phd thesis, Univerzitet u Novom Sadu, Prirodno-matematički fakultet u Novom Sadu, 2013. https://www.cris.uns.ac.rs/record.jsf?recordId=83535&source=NDLTD&language=en.

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The  research  topic  involves  personalization  of  an  e‐learning  system  based  oncollaborative  tagging  techniques  integrated  in  a  recommender  system.  Collaborative  tagging systems allow users to upload their resources, and to label them with arbitrary words, so‐called tags.  The  systems  can  be  distinguished  according  to  what  kind  of  resources  are  supported. Besides helping user to organize his or her personal c

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Nagi, Mohamad. "Integrating Network Analysis and Data Mining Techniques into Effective Framework for Web Mining and Recommendation. A Framework for Web Mining and Recommendation." Thesis, University of Bradford, 2015. http://hdl.handle.net/10454/14200.

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The main motivation for the study described in this dissertation is to benefit from the development in technology and the huge amount of available data which can be easily captured, stored and maintained electronically. We concentrate on Web usage (i.e., log) mining and Web structure mining. Analysing Web log data will reveal valuable feedback reflecting how effective the current structure of a web site is and to help the owner of a web site in understanding the behaviour of the web site visitors. We developed a framework that integrates statistical analysis, frequent pattern mining, clusterin

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Guerrini, Gabriele. "Analysis, design and implementation of a parking recommendation system applying machine learning techniques." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2021. http://amslaurea.unibo.it/23162/.

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Nowadays, smart city and urban mobility topics are focusing growing interest for business and R\&D purposes both, and one of its trendy application regards the study and the realization of parking recommendation systems. In our case, a parking recommendation system is going to be developed for the city of Bologna. After a brief revision of similar proposed solutions and their approaches and findings, a first data analysis phase is going to be executed to explore the data and to mine any useful information about the parking behavior. Then, once the adopted forecasting model has been exposed,

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Cabir, Hassane Natu Hassane. "A Comparison Of Different Recommendation Techniques For A Hybrid Mobile Game Recommender System." Master's thesis, METU, 2012. http://etd.lib.metu.edu.tr/upload/12615173/index.pdf.

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As information continues to grow at a very fast pace, our ability to access this information effectively does not, and we are often realize how harder is getting to locate an object quickly and easily. The so-called personalization technology is one of the best solutions to this information overload problem: by automatically learning the user profile, personalized information services have the potential to offer users a more proactive and intelligent form of information access that is designed to assist us in finding interesting objects. Recommender systems, which have emerged as a solution to

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Videla, Cavieres Iván Fernando. "Improvement of recommendation system for a wholesale store chain using advanced data mining techniques." Tesis, Universidad de Chile, 2015. http://repositorio.uchile.cl/handle/2250/133522.

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Magíster en Gestión de Operaciones<br>Ingeniero Civil Industrial<br>En las empresas de Retail, las áreas de Customer Intelligence tienen muchas oportunidades de mejorar sus decisiones estratégicas a partir de la información que podrían obtener de los registros de interacciones con sus clientes. Sin embargo se ha convertido en un desafío poder procesar estos grandes volúmenes de datos. Uno de los problemas que se enfrentan día a día es segmentar o agrupar clientes. La mayoría de las empresas generan agrupaciones según nivel de gasto, no por similitud en sus canastas de compra, como propone la

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Holländer, John. "Investigating the performance of matrix factorization techniques applied on purchase data for recommendation purposes." Thesis, Malmö högskola, Fakulteten för teknik och samhälle (TS), 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:mau:diva-20624.

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Automated systems for producing product recommendations to users is a relatively new area within the field of machine learning. Matrix factorization techniques have been studied to a large extent on data consisting of explicit feedback such as ratings, but to a lesser extent on implicit feedback data consisting of for example purchases.The aim of this study is to investigate how well matrix factorization techniques perform compared to other techniques when used for producing recommendations based on purchase data. We conducted experiments on data from an online bookstore as well as an onlin

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Bambia, Meriam. "Jointly integrating current context and social influence for improving recommendation." Thesis, Toulouse 3, 2017. http://www.theses.fr/2017TOU30110/document.

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La diversité des contenus recommandation et la variation des contextes des utilisateurs rendent la prédiction en temps réel des préférences des utilisateurs de plus en plus difficile mettre en place. Toutefois, la plupart des approches existantes n'utilisent que le temps et l'emplacement actuels séparément et ignorent d'autres informations contextuelles sur lesquelles dépendent incontestablement les préférences des utilisateurs (par exemple, la météo, l'occasion). En outre, ils ne parviennent pas considérer conjointement ces informations contextuelles avec les interactions sociales entre les u

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Książki na temat "RECOMMENDATION TECHNIQUES"

Obuhova, Galina, and Galina Klimova. Fundamentals of public communication skills: practical recommendations. INFRA-M Academic Publishing LLC., 2021. http://dx.doi.org/10.12737/1090527.

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The textbook discusses the methodological foundations of the preparation and presentation of public speeches in various fields of activity, including business. The factors influencing the skill of the speaker are considered. Recommendations are given on the technique of conducting various types of public speeches and practical techniques of audience ownership are shown. Special attention is paid to the methods of establishing contact between the speaker and the audience and the psychological influence of the speaker on the audience. Practical recommendations and exercises for improving the spe

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Council of Europe. Committee of Ministers. Special investigation techniques in relation to serious crimes including acts of terrorism: Recommendation Rec(2005)10 adopted by the Committee of Ministers of the Council of Europe on 20 April 2005 and explanatory memorandum. Council of Europe Publishing, 2005.

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Myagkov, Aleksandr. Indirect methods in sensitive research. INFRA-M Academic Publishing LLC., 2024. http://dx.doi.org/10.12737/2110854.

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The monograph examines the theoretical, methodological and methodological problems of obtaining sincere answers from respondents in sensitive surveys. Based on the materials of foreign scientific sources and experimental studies conducted by the author, various indirect methods of working with sensitive questions are analyzed: RRT models, non-randomized survey techniques, the technique of unpaired numbers, nominative technique, bogus pipeline procedure, etc. The normative content of these methods, their organizational, technical and statistical features are investigated. Some recommendations a

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Wiggers, Willem J. H. Drafting contracts: Techniques, best practice rules and recommendations related to contract drafting. Kluwer, 2011.

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author, Maslov D. E., and Russia (Federation). Ministerstvo vnutrennikh del. Nizhegorodskai︠a︡ akademii︠a︡, eds. I︠U︡ridicheskai︠a︡ rekomendat︠s︡ii︠a︡: Doktrina, praktika, tekhnika : monografii︠a︡ = Legal Recommendation : Doctrine, Practice, Technique : Monograph. Prospekt, 2021.

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International Telegraph and Telephone Consultative Committee. Plenary Assembly. Red book.: Open systems interconnection (OSI) system description techniques : recommendations X.200-X.250. International Telecommunication Union, 1985.

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Rhodes, Tina Gabriele. Investigation of a relaxation technique: Personal control expectancies and adherence to practice recommendations. University of Surrey Roehampton, 2002.

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Filippov, Mihail, Svetlana Savel'eva, and Elena Belous. Conflicts among adolescents and mediation techniques for their resolution. INFRA-M Academic Publishing LLC., 2025. https://doi.org/10.12737/2141118.

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The textbook reveals the main causes, conditions and current techniques for overcoming conflicts among adolescents in the education system. The issues of conflict prevention and ways of their resolution are considered. The analysis of the conflict behavior of adolescents in educational institutions and recommendations for its resolution are given. The manual also includes technologies for studying and diagnosing conflict situations, contains specific descriptions of diagnostic techniques and mediation techniques, features of their implementation, generalization, analysis and data processing. M

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C, Rigg J., International Union of Pure and Applied Chemistry. Commission on Quantities & Units in Clinical Chemistry., and International Federation of Clinical Chemistry. Committee on Quantities & Units., eds. Compendium of terminology and nomenclature of properties in clinical laboratory sciences: Recommendations 1995. Blackwell Science, 1995.

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World Health Organization (WHO). WHO recommendations on rabies post-exposure treatment and the correct technique of intradermal immunization against rabies. Stationery Office, 1999.

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Części książek na temat "RECOMMENDATION TECHNIQUES"

Singh, Gambhir, Anupam Kumar Saini, Vishal Pratap Singh, Muzammil Abedin, and Hammad Alam. "Movie recommendation system using AI." In Intelligent Computing and Communication Techniques. CRC Press, 2025. https://doi.org/10.1201/9781003530176-63.

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Jingxian, Huang. "Research on Intelligent Recommendation Method of e-commerce Hot Information Based on User Interest Recommendation." In Simulation Tools and Techniques. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-72795-6_13.

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Kumar, Praharsh, Abhishek Anand, Saurabh Ramesh Umbarkar, Suraj Vishwakarma, M. Ahmer Usmani, and Vivek Solavande. "Apparel recommendation system using image processing." In Intelligent Computing and Communication Techniques. CRC Press, 2025. https://doi.org/10.1201/9781003530176-61.

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Raghuwanshi, Sandeep K., and R. K. Pateriya. "Collaborative Filtering Techniques in Recommendation Systems." In Data, Engineering and Applications. Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-6347-4_2.

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Jiang, Feng, Min Gao, Qingyu Xiong, Junhao Wen, and Yi Zhang. "Robust Social Recommendation Techniques: A Review." In Socially Aware Organisations and Technologies. Impact and Challenges. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-42102-5_6.

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Singh, Sanika, Aman Anand, Tanupriya Choudhury, Pankaj Sharma, and Ved P. Mishra. "Extensive Review on Product Recommendation Techniques." In Data Driven Approach Towards Disruptive Technologies. Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-15-9873-9_43.

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Vaishnani, Darsh, Rohan Vaghela, Vraj Patel, et al. "Deep Learning Techniques for Apparel Recommendation." In Lecture Notes in Networks and Systems. Springer Nature Singapore, 2025. https://doi.org/10.1007/978-981-96-3361-6_5.

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Acharya, Soumya S., Nandita Nupur, Priyabrat Sahoo, and Paresh Baidya. "Mood-Based Movie Recommendation System." In Biologically Inspired Techniques in Many Criteria Decision Making. Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-16-8739-6_13.

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Wang, Xiaofeng, Dongming Tang, Hui Zheng, and Ke Zhang. "Study and Implementation of Minority Mobile Application Recommendation Software." In Simulation Tools and Techniques. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-32216-8_54.

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Radja, Priyanka. "Personalized Recommendation Techniques in Social Tagging Systems." In Soft Computing Systems. Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-13-1936-5_4.

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Streszczenia konferencji na temat "RECOMMENDATION TECHNIQUES"

Babu, Sallagundla, Mallavarapu Vivek, Dammu Jaya Bhargav Nand, and Gandham Kumar N. S. L. Prakash. "Crop Recommendation Using Supervised Learning Techniques." In 2024 International Conference on Computing and Intelligent Reality Technologies (ICCIRT). IEEE, 2024. https://doi.org/10.1109/iccirt59484.2024.10922060.

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Zhou, Jing, Yang Zheng, Songbin Yu, Zhijun Yan, and Huishen Yuan. "Commodity Recommendation Techniques Based on Multimodal Data." In 2024 3rd International Conference on Artificial Intelligence and Autonomous Robot Systems (AIARS). IEEE, 2024. http://dx.doi.org/10.1109/aiars63200.2024.00007.

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Pal, Abhishek Kumar, Aditya Raj Parashar, Arjun Yadav, Anurag Yadav, and Madan Pachori. "Yoga, Recommendation, System using, Machine Learning Techniques." In 2024 1st International Conference on Advances in Computing, Communication and Networking (ICAC2N). IEEE, 2024. https://doi.org/10.1109/icac2n63387.2024.10895752.

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Baadou, Sana, Salim Lafdoul, and Ahmed Bendahmane. "Intelligent Recommendation Systems: Literature Review on Recommendation Techniques and Their Use in Education." In 2024 Mediterranean Smart Cities Conference (MSCC). IEEE, 2024. http://dx.doi.org/10.1109/mscc62288.2024.10697042.

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Nitasha, Aniket Kumar Pandey, Ankit Yadav, Subrat Mishra, and Medhanshi. "Enhancing Movie Recommendation Efficiency Using Ensemble Learning Techniques." In 2024 International Conference on Emerging Innovations and Advanced Computing (INNOCOMP). IEEE, 2024. http://dx.doi.org/10.1109/innocomp63224.2024.00094.

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Vaddineni, Sai Pranathi, Uday Karthik Pillarisetty, Kalyan Ram, Yaswanth Rayapati, and Syed Shareefunnisa. "Integrating Multiple Recommendation Techniques for Enhanced Anime Discovery." In 2024 8th International Conference on Inventive Systems and Control (ICISC). IEEE, 2024. http://dx.doi.org/10.1109/icisc62624.2024.00045.

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Özlü, Özgür Anıl, Günce Keziban Orman, and Sultan N. Turhan. "Exploring Graph-Based Techniques in Job Recommendation Systems." In 2024 IEEE 12th International Conference on Intelligent Systems (IS). IEEE, 2024. http://dx.doi.org/10.1109/is61756.2024.10705169.

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Aziz, Mohammad Tarek, Mohammad Kamal Uddin, Tanjim Mahmud, Dilbar Abdullayeva Urazbayeva, Sha Md Farid, and Mohammad Shamsul Arefin. "Efficient Job Recommendation Framework Using Genetic Optimization Techniques." In 2025 International Conference on Electrical, Computer and Communication Engineering (ECCE). IEEE, 2025. https://doi.org/10.1109/ecce64574.2025.11013407.

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Tiwari, Mohit, Aryan Kumar, and B. Bharathi. "Price Recommendation For E-Commerce Using ML Techniques." In 2024 Intelligent Systems and Machine Learning Conference (ISML). IEEE, 2024. https://doi.org/10.1109/isml60050.2024.11007352.

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Herath, Tharindu, and Dinesh Asanka. "Robotic Process Automation Activity Recommendation using NLP Techniques." In 2025 5th International Conference on Advanced Research in Computing (ICARC). IEEE, 2025. https://doi.org/10.1109/icarc64760.2025.10963182.

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Raporty organizacyjne na temat "RECOMMENDATION TECHNIQUES"

A, Bengolea, Chamorro F, Ozon N, Catalano HN, and Izcovich A. Effectiveness and safety of utilizing imaging techniques to guide treatment in patients with venous thromboembolism. Epistemonikos Interactive Evidence Synthesis, 2023. http://dx.doi.org/10.30846/ies.2b03926263.v1.

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Objective The objective of this systematic review is to perform a comprehensive evaluation of the efficacy and safety of the use of imaging to determine the duration of anticoagulant treatment in patients with thrombosis of any cause (idiopathic, resolved secondary or chronic) who have completed a period of 3 to 6 months of oral anticoagulant treatment. Methods In order to identify randomized clinical trials that evaluate our question of interest, we performed exhaustive searches in Epistemonikos and PubMed, from the date of creation of each source until February 2024. Additionally, we conside

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Deppe, Sahar. AI-based reccomendation system for industrial training. Kompetenzzentrum Arbeitswelt.Plus, 2023. http://dx.doi.org/10.55594/vmtx7119.

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Recommendation systems have become a main part of e-learning, reshaping the landscape of digital education. In an era marked by the proliferation of online courses, diverse learning materials, and users with varying needs, these systems offer a dynamic solution. This paper explores recommendation techniques and their role in e-learning and web-based training, delving into their mechanisms, challenges, and opportunities. Moreover, future directions of these systems in e-learning, including the integration of artificial intelligent and emerging technologies, and the quest for transparency and pr

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P. D. Mattie, J. A. McNeish, D. S. Sevougian, and R. W. Andrews. Methods and Techniques Used to Convey Total System Performance Assessment Analyses and Results for Site Recommendation at Yucca Mountain, Nevada, USA. Office of Scientific and Technical Information (OSTI), 2001. http://dx.doi.org/10.2172/786563.

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Pasupuleti, Murali Krishna. AI-Driven Marketing Innovations: Personalization and Ethics in the Digital Era. National Education Services, 2025. https://doi.org/10.62311/nesx/rr625.

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Abstract: This article explores the transformative impact of artificial intelligence (AI) on digital marketing, focusing on strategies for delivering personalized content and ensuring ethical advertising. By leveraging AI, marketers can now analyze consumer behavior with precision, enabling targeted content, automated ad placement, and real-time adjustments that enhance user engagement and conversions. The Article examines foundational AI techniques, such as recommendation engines, predictive analytics, and natural language processing, which drive personalization at scale. Additionally, it add

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Eiber. L51786 Development of Optimized Nondestructive Inspection Methods for Hot Tap Branch Connection Welds. Pipeline Research Council International, Inc. (PRCI), 1998. http://dx.doi.org/10.55274/r0010388.

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In the first two phases of this project, the accuracy and reliability of both conventional and more advanced nondestructive inspection techniques were evaluated by way of a round-robin program of blind inspections The results indicate that there is much variability in the accuracy and reliability of discontinuity detection and sizing depending on details of the NDT procedures adopted, which includes specification of equipment, techniques, calibration methods, and reporting requirements. In Phase III, optimized procedures for sleeve fillet welds and a limited number of branch groove welds were

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Ulrich, Timothy J. II. Recommendations for acoustic techniques that meet facility requirements. Office of Scientific and Technical Information (OSTI), 2012. http://dx.doi.org/10.2172/1052352.

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Balick, Lee K., John R. Hummel, James A. Smith, and Daniel S. Kimes. One-Dimensional Temperature Modeling Techniques. Review and Recommendations. Defense Technical Information Center, 1990. http://dx.doi.org/10.21236/ada231098.

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GAFNER, STEFAN. Black Cohosh Adulteration Laboratory Guidance Document. ABC-AHP-NCNPR Botanical Adulterants Prevention Program, 2015. http://dx.doi.org/10.59520/bapp.lgd/fbaj9867.

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In recent years, adulteration of black cohosh roots and rhizomes (Actaea racemosa, Ranunculaceae) has become more apparent. Adulteration predominantly occurs with Chinese species of Actaea such as A. heracleifolia, A. dahurica, and A. cimicifuga (all known by the common name Chinese cimicifuga and by the Chinese name of sheng ma). Additionally, the Chinese cimicifuga (sheng ma) market is commonly adulterated with Serratula chinensis (guang dong sheng ma [Asteraceae]). Adulteration has also been reported with North American Actaea species growing in the same area as black cohosh, such as A. pac

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Iseley, D. T., and D. H. Cowling. L51697 Obstacle Detection to Facilitate Horizontal Directional Drilling. Pipeline Research Council International, Inc. (PRCI), 1994. http://dx.doi.org/10.55274/r0010134.

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The horizontal directional drilling (HDD) technique is specially suited for pipeline crossings of waterways, beaches, roads, vulnerable natural regions, railroads and airports. The HDD method is a two-stage process consisting of navigating a drill stem underground along a predetermined design route and the pulling back of the product pipe through the prepared hole. One of the major problems faced in HDD projects is subsurface exploration and locating of existing underground obstacles. HDD equipment must avoid these obstacles if at all possible. This study was conducted to: 1. Determine the sta

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