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Статті в журналах з теми "Group Recommendation System"
Dewi, Ratih Kartika. "Group Decision Support System based on AHP-TOPSIS for Culinary Recommendation System." Jurnal Ilmu Komputer dan Informasi 12, no. 2 (July 8, 2019): 85. http://dx.doi.org/10.21609/jiki.v12i2.729.
Повний текст джерелаDewi, Ratih Kartika, Eriq Muhammad Adams Jonemaro, Agi Putra Kharisma, Najla Alia Farah, and Mury Fajar Dewantoro. "TOPSIS for mobile based group and personal decision support system." Register: Jurnal Ilmiah Teknologi Sistem Informasi 7, no. 1 (February 15, 2021): 43. http://dx.doi.org/10.26594/register.v7i1.2140.
Повний текст джерелаKim, Jae Kyeong, Hyea Kyeong Kim, Hee Young Oh, and Young U. Ryu. "A group recommendation system for online communities." International Journal of Information Management 30, no. 3 (June 2010): 212–19. http://dx.doi.org/10.1016/j.ijinfomgt.2009.09.006.
Повний текст джерелаThenmozhi, M., and T. P. "Group Coupon Recommendation System for Mobile Users." International Journal of Computer Applications 143, no. 10 (June 17, 2016): 31–36. http://dx.doi.org/10.5120/ijca2016910379.
Повний текст джерелаLiu, Xuehong, and Xuefeng Ding. "User Privacy Protection Algorithm Of Perceptual Recommendation System Based On Group Recommendation." International Journal of Autonomous and Adaptive Communications Systems 13, no. 2 (2020): 1. http://dx.doi.org/10.1504/ijaacs.2020.10031495.
Повний текст джерелаDing, Xuefeng, and Xuehong Liu. "User privacy protection algorithm of perceptual recommendation system based on group recommendation." International Journal of Autonomous and Adaptive Communications Systems 13, no. 2 (2020): 135. http://dx.doi.org/10.1504/ijaacs.2020.109809.
Повний текст джерелаDewi, Ratih Kartika, Mahardeka Tri Ananta, Lutfi Fanani, Komang Candra Brata, and Nurizal Dwi Priandani. "The Development of Mobile Culinary Recommendation System Based on Group Decision Support System." International Journal of Interactive Mobile Technologies (iJIM) 12, no. 3 (July 20, 2018): 209. http://dx.doi.org/10.3991/ijim.v12i3.7799.
Повний текст джерелаRavi, Logesh, and Subramaniyaswamy Vairavasundaram. "A Collaborative Location Based Travel Recommendation System through Enhanced Rating Prediction for the Group of Users." Computational Intelligence and Neuroscience 2016 (2016): 1–28. http://dx.doi.org/10.1155/2016/1291358.
Повний текст джерелаMeena, Ritu, and Sonajharia Minz. "Group Recommender Systems – An Evolutionary Approach Based on Multi-expert System for Consensus." Journal of Intelligent Systems 29, no. 1 (November 20, 2018): 1092–108. http://dx.doi.org/10.1515/jisys-2018-0081.
Повний текст джерелаChen, Yen-Liang, Li-Chen Cheng, and Ching-Nan Chuang. "A group recommendation system with consideration of interactions among group members." Expert Systems with Applications 34, no. 3 (April 2008): 2082–90. http://dx.doi.org/10.1016/j.eswa.2007.02.008.
Повний текст джерелаДисертації з теми "Group Recommendation System"
Smaaberg, Simen Fivelstad. "Context-Aware Group Recommendation Systems." Thesis, Norges teknisk-naturvitenskapelige universitet, Institutt for datateknikk og informasjonsvitenskap, 2014. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-27328.
Повний текст джерелаRicardo, de Melo Queiroz Sérgio. "Group recommendation strategies based on collaborative filtering." Universidade Federal de Pernambuco, 2003. https://repositorio.ufpe.br/handle/123456789/2528.
Повний текст джерелаRicardo de Melo Queiroz, Sérgio; de Assis Tenório Carvalho, Francisco. Group recommendation strategies based on collaborative filtering. 2003. Dissertação (Mestrado). Programa de Pós-Graduação em Ciência da Computação, Universidade Federal de Pernambuco, Recife, 2003.
Coulibaly, Adama. "Décision de groupe, Aide à la facilitation : ajustement de procédure de vote selon le contexte de décision." Thesis, Toulouse 1, 2019. http://www.theses.fr/2019TOU10011/document.
Повний текст джерелаFacilitation is a central element in decision-making, especially when using new technology tools. The facilitator, to make his task easy, needs voting solutions to decide between decision-makers in order to reach conclusions in a decision-making process. A voting procedure consists of determining from a method the winner of a vote. There are several voting procedures, some of which are difficult to explain and which may elect different candidate/options/alternatives proposed. The best choice is the one whose election is easily accepted by the group. Voting in social choice theory is a widely studied discipline whose principles are often complex and difficult to explain at a decision-making meeting. Recommendation systems are becoming more and more popular in all fields of science. They can help users who do not have sufficient experience or competence to evaluate large numbers of existing voting procedures. A recommendation system can lighten the facilitator's workload in finding an appropriate voting procedure based on the decision-making context. The objective of this research work is to design such recommendation system. This work is in the field of group decision support. The issue is to contribute to the development of a Group Decision Support System (GDSS). The solution will have to be integrated into the software platform currently being developed at IRITGRUS: GRoUp Support
Scholz, Donald P. "Performance Criteria Recommendations for Mortars Used in Full-Depth Precast Concrete Bridge Deck Panel Systems." Thesis, Virginia Tech, 2004. http://hdl.handle.net/10919/36194.
Повний текст джерелаMaster of Science
Kannenberg, Ernst August. "The suitability of a system of group taxation for South Africa, with specific reference to the recommendations of the Katz Commission." Thesis, Stellenbosch : Stellenbosch University, 1999. http://hdl.handle.net/10019.1/51517.
Повний текст джерелаENGLISH ABSTRACT: The current South African tax dispensation does not make provision for a system of group taxation, which gives rise to various tax anomalies. The Katz Commission recommended the implementation of a consolidation system of group taxation in their third interim report. This study investigates the issue of group taxation with the objective of commenting on the Katz Commission's recommendation. Chapter 1 explains the purpose of a system of group taxation and discusses the different forms of group taxation. Furthermore, the theoretical norms or canons are described which can be used to evaluate the current tax treatment of groups as well as the different forms of group taxation. Chapter 2 investigates the current tax treatment of groups by focussing on the tax implications of various intra-group transactions. It is found that the current tax treatment of groups does not satisfy the canons of equity, neutrality, efficiency of tax collection, low administration cost and certainty. Although the absence of a system of group taxation may contribute to technical simplicity, such an absence also leads to complex tax schemes that attempt to exploit favourable tax anomalies or avoid unfavourable anomalies. Chapter 3 exammes certain Issues which may render a system of group taxation unnecessary or undesirable, even if such a system leads to better compliance with the canons of taxation. The conclusion is reached that none of these issues will cause such a result. With regard to the issue of divisionalisation as an alternative to group taxation, it is found that section 39 of the Taxation Laws Amendment, No. 20 of 1994 does not provide an accessible mechanism for divisionalisation. Furthermore, groups may be preferred over divisionalised companies for various commercial and legal reasons. With regard to the issue of limited liability of individual group companies (a benefit which is not available to individual divisions of a single company) it is found that group companies rarely abuse this benefit. In addition, a system of group taxation will complement the concept of limited liability in promoting economic growth. With regard to the issue of concentration of economic control and ownership, the conclusion is reached that group taxation will not lead to further concentration of economic control, as the intra-group shareholding required for group tax treatment will greatly exceed the intra-group shareholding necessary for economic control. A system of group taxation may even lead to the broadening of economic ownership by enabling minority shareholdings in group companies which would otherwise be structured as divisions of existing companies due to tax considerations. Chapter 4 compares the loss transfer system of group taxation with the consolidation system, using the canons of taxation as a reference framework. Because a loss transfer system is similar to the current tax treatment of groups, in the sense that both dispensations treat individual group companies as separate taxable entities, the current tax treatment of groups is included in the above mentioned comparison by implication. It is found that a consolidation system will satisfy the canons of taxation the best. Although such a system carries the risk of undue complexity, it should be possible to design and implement a specific system which will fall within the administrative capabilities of both taxpayers and tax authorities. Chapter 5 examines key recommendations of the Katz commission with regard to group taxation. The writer expresses his agreement with the commission's conclusion that a consolidation system of group taxation should be implemented gradually. Certain adjustments to the commission's recommendations are suggested, which will facilitate quicker implementation and increased simplicity. The current tax treatment of groups leads to tax anomalies which are highly unsatisfactory. From a theoretical as well as a practical perspective, the implementation of a consolidation system of group taxation will represent a significant improvement to the South African tax dispensation.
AFRIKAANSE OPSOMMING: Suid-Afrika beskik tans nie oor 'n stelsel van groepbelasting nie, wat aanleiding gee tot verskeie belastinganomaliee. Die Katz-kommissie het die implementering van 'n gekonsolideerde stelsel van groepbelasting aanbeveel in hulle derde tussentydse verslag. Hierdie studie ondersoek die aangeleentheid van groepbelasting met die doel om kommentaar te !ewer op die Katz-kommissie se voorstelle in hierdie verband. In Hoofstuk 1 word die doel van 'n stelsel van groepbelasting verduidelik, en die verskillende vorme van groepbelasting bespreek. V erder word die teoretiese norme beskryf waaraan die huidige belastinghantering van groepe en die verskillende vorme van groepbelasting gemeet kan word. In Hoofstuk 2 word die huidige belastinghantering van groepe ondersoek deur te fokus op die belastingimplikasies van 'n verskeidenheid intra-groep transaksies. Dit word bevind dat die huidige belastinghantering van groepe nie lei tot billikheid, neutraliteit, effektiewe invordering van die belastinglas, lae administrasiekoste en sekerheid nie. En alhoewel die gebrek aan 'n stelsel van groepbelasting bydra tot tegniese eenvoud, lei dit terselfdetyd tot ingewikkelde, belastinggedrewe skemas wat poog om gunstige belastinganomaliee te benut en om ongunstige belastinganomaliee te vermy. In Hoofstuk 3 word sekere aangeleenthede ondersoek wat moontlik 'n stelsel van groepbelasting onnodig of onwenslik sal maak, selfs al sou so 'n stelsellei tot 'n meer gebalanseerde bevrediging van die teoretiese belastingnorme. Die slotsom word bereik dat geeneen van hierdie aangeleenthede we! so 'n resultaat sal he nie. Met betrekking tot divisionalisering as 'n altematief vir groepbelasting, word beslis dat artikel 39 van die Wysigingswet op Belastingwette, No. 20 van 1994 nie 'n toeganglike meganisme daarstel vir die divisionalisering van bestaande groepe nie. Uit 'n kommersiele en regsoogpunt bestaan daar boonop verskeie redes waarom groepe bo gedivisionaliseerde maatskappye verkies word. Met betrekking tot die beperkte aanspreeklikheid van afsonderlike groepmaatskappye ('n voordeel wat nie tot die beskikking is van divisies van 'n enkele maatskappy nie), word bevind dat groepe in praktyk selde hierdie voordeel misbruik of selfs benut. Voorts sal 'n stelsel van groepbelasting die konsep van beperkte aanspreeklikheid komplimenteer in die bevordering van ekonomiese groei. Met betrekking tot die konsentrasie van ekonomiese beheer en eienaarskap, word beslis dat 'n stelsel van groepbelasting nie die verdere konsentrasie van ekonomiese beheer sal aanhelp nie, aangesien die kwalifiserende aandeelhouding wat vir groepbelastinghantering vereis sal word, die aandeelhouding wat nodig is vir ekonomiese beheer ver sal oorskry. 'n Stelsel van groepbelasting mag voorts hydra tot die verbreding van aandeeleienaarskap, deurdat buiteaandeelhouers direkte belange sal kan opneem in ondernemings wat andersins gestruktureer sou word as divisies van bestaande maatskappye. In Hoofstuk 4 word verliesoordragstelsels en gekonsolideerde stelsels van groepbelasting in die algemeen vergelyk, met die belastingnorme as 'n verwysingsraamwerk. Aangesien 'n verliesoordragstelsel soortgelyk is aan die huidige belastinghantering van groepe, in die sin dat albei bedelings groepmaatskappye as afsonderlike belastingentiteite hanteer, word die huidige belastinghantering van groepe by implikasie ingesluit in die vergelyking. Die slotsom word bereik dat 'n gekonsolideerde stelsel van groepbelasting die mees bevredigende stelsel is in terme van 'n gebalanseerde voldoening aan die belastingnorme. Alhoewel 'n gekonsolideerde stelsel die risiko van kompleksiteit inhou, is dit moontlik om 'n spesifieke stelsel op sodanige wyse te ontwerp en implementeer dat dit wel administreerbaar sal wees. In Hoofstuk 5 word sleutelaanbevelings van die Katz-kommissie met betrekking tot groepbelasting ondersoek. Die skrywer spreek sy instemming uit met die kommissie se voorstelle vir die geleidelike implementering van 'n gekonsolideerde stelsel van groepbelasting. Sekere wysigings word aangebring aan die kommissie se voorstelle, ten einde verdere eenvoud en spoediger implementering teweeg te bring. W anneer die belastinganomaliee as gevolg van die huidige belastinghantering van groepe oorweeg word, is dit duidelik dat die huidige situasie onhoudbaar is. Uit 'n teoretiese en praktiese oogpunt, sal die implementering van 'n gekonsolideerde stelsel van groepbelasting 'n beduidende verbetering van die Suid-Afrikaanse belastingbedeling meebring.
Stein, Jacob. "Supporting feature model configuration based on multi-stakeholder preferences." reponame:Biblioteca Digital de Teses e Dissertações da UFRGS, 2015. http://hdl.handle.net/10183/117277.
Повний текст джерелаFeature model con guration is known to be a hard, error-prone and timeconsuming activity. This activity gets even more complicated when it involves multiple stakeholders in the con guration process. Research work has proposed approaches to aid multi-stakeholder feature model con guration, but they rely on systematic processes that constraint decisions of some of the stakeholders. In this dissertation, we propose a novel approach to improve the multi-stakeholder con guration process, considering stakeholders' preferences expressed through both hard and soft constraints. Based on such preferences, we recommend di erent product con gurations using di erent strategies from the social choice theory. Our approach is implemented in a tool named SACRES, which allows creation of stakeholder groups, speci cation of stakeholder preferences over a con guration and generation of optimal con guration. We conducted an empirical study to evaluate the e ectiveness of our strategies with respect to individual stakeholder satisfaction and fairness among all stakeholders. The obtained results provide evidence that particular strategies perform best with respect to group satisfaction, namely average and multiplicative, considering the scores given by the participants and computational complexity. Our results are relevant not only in the context software product lines, but also in the context of social choice theory, given the instantiation of social choice strategies in a practical problem.
Wang, Yi-Ming, and 汪怡銘. "Feature Importance Evaluation under Fuzzy Group Based Recommendation System." Thesis, 2019. http://ndltd.ncl.edu.tw/handle/8gkzc9.
Повний текст джерела國立臺灣科技大學
工業管理系
107
This research aims to propose a fuzzy group based recommendation system structure, which generates feature importance from dataset using feature selection methods. Feature importance will be considered as the influence level of the group based purchasing behavior, and further be used to calculate the rating that quantifies customers’ buying desire to a certain merchandise. Under the simulation of recommendation mechanism, this research utilizes the ratio of customers that are covered by the proposed model’s prediction with their purchased merchandise (coverage rate), evaluating the effect caused by different feature selection methods on the proposed structure. Financial dataset and shopping transaction dataset are also used to verify the performance. The proposed feature selection methods are: Fisher Discriminant Ratio (FDR), Fisher Discriminant Ratio with Membership Degree (FDRMD) and Random Forest (RF). The results indicate that FDR is capable of discovering singular customer groups, which refers to the few customer groups with extremely high coverage rate based on the recommendation, comparing to other customer groups with low coverage rate. For real world applications, identifying singular customers can benefit the companies in recommendation budget optimization problems or accurate promotions.
Hong, Pei-Ru, and 洪佩如. "A Book Recommendation System to Group Based on User Influence." Thesis, 2014. http://ndltd.ncl.edu.tw/handle/bczq39.
Повний текст джерела國立交通大學
資訊管理研究所
102
With the development of internet, users not only receive information passively but also share their own opinion and thinking in the social network. Accordingly, users’ preferences for items may be affected by other users through opinion sharing and social interactions in the network. Moreover, users with similar preferences usually form a group to share items with each other, and thus users’ preferences may be affected by group members. Existing researches often focus on analyzing personal preferences, and group recommendation approaches considering the influences of group members are relatively few. In this work, we investigate group recommendation approaches for recommending books of the website-Goodreads, which is a social network website for sharing interests (ratings) and opinions to books. We propose novel group recommendation approach by analyzing groups’ preferences based on three types of group member influences - Group Member Influence, Review Influence and Recommendation Influence. LDA (Latent Dirichlet Allocation) is adopted to derive the latent topic features of book contents. The proposed approach then integrates member influences to derive a group’s topic profiles from the topic features of books collected by the group. Finally, the proposed approach integrates members’ ratings on books and similarity measures between book topic features and group topic profile to predict the group’s preference scores on books. The experimental results show that our proposed approach can effectively improve the quality of recommendations.
Wang, Wei. "Enhanced group recommender system and visualization." Thesis, 2016. http://hdl.handle.net/10453/62409.
Повний текст джерелаRequirement of group recommender systems (GRSs) is experiencing a dramatic growth due to intelligent services being applied more broadly and involved in more and more domains. However, effectivity and interpretability are still two challenges in GRSs. A typical scenario is: a group is formed randomly without active organizing in advance and sufficient negotiation between members before recommending, such as e-shopping and e-tourism. Therefore, deeply modeling the group profile is the first key part to generate recommendations. Moreover, accurately predicting should be a problem under biased and limited information provided by users. The interpretability challenge is that most of GRSs are black boxes for providing no necessary explanation of recommendations but only a list. It is quite important to convince members to make them understand why the specific recommendations are reasonable. Thus, explaining the reason generated recommendations and relationships between members needs to be investigated. This research aims to handle these two challenges in both theoretical and practical aspects. A novel group recommendation approach is developed and aims to maximize satisfaction within random groups by modeling the group profiles through the analysis of contributed member ratings alone. First, the Contribution Score is defined to numerically measure each member’s importance in terms of the sub-rating matrix which makes it practical even when the matrix is highly incomplete and sparse. Second, a local collaborative filtering method is developed to address the biased rating problem caused by severe preference conflicting in random groups. An adaptive average rating calculating model is proposed taking into consideration of the target item by reducing the set to those which are highly relevant to it. By integrating these two models, a Contribution Score-based Group Recommendation (CS-GR) approach is developed to efficiently depict groups. Also, a novel hierarchy graph-based visualization method, based on data visualization techniques, which are powerful tools to offer intuitive abstractions of concepts, is suggested to offer explanations for users. First a higher level of abstraction of the overall recommender modules, such as group profile modeling and prediction calculating, is presented using a hierarchy graph. To do this, all the entities involved in a group recommender process are summarized and visualized as nodes in the graph and the edges in the graph represent information inherited. Second, the layout provides detailed information for individual members to track their influences in the system by adding pie charts at each single node to show individual influences for all involved members. This enables members to track and compare their influences with others in every single procedure. This research provides the GRSs effectivity for the biased and sparse information which can be handled to model the group and generate the predictions. The scalability and efficiency are also guaranteed because only rating information is needed and matrix decomposition technique is employed. The visualization is used to provide both overall and detailed explanation for users.
Chen, Ming-Fong, and 陳明豐. "The Development of a Recommendation System Based on Ontology: An Example of Outbound Group Package Tour." Thesis, 2007. http://ndltd.ncl.edu.tw/handle/24937132216266515275.
Повний текст джерела國立嘉義大學
資訊管理學系碩士班
95
Online travel web sites gain its popularity among customers. More and more customers tend to buy travel products online. These kind of commercial web sites offer wide-ranged information of traveling-related products and they provide one-stop buys for customers. Nevertheless, customers are required to spend time on searching and finding right products due to the problem of information overload. In general cases, customer decision-making composes sequential processes in terms of determining needs, searching available information, evaluating information, making buying decision and determining post-purchase behavior. With regard to this framework, this study takes the notion of the literature in the context of Internet marketing that signifying product characteristics and web site profiles do major influences on shopper’s buying decision-making for systematic investigation. It is also noted that customers’ lifestyle can be a norm to distinctively segment customers. With the main goal to improve the search effectiveness of an intelligent agent, customers’ knowledge of search is well empirically acquired and organized in a machine-readable form based on ontology. The case of outbound group package tour in Taiwan is selected for further exploration due to its annually huge sales. Travel experts are invited to provide interrelated knowledge regarding this domain and further verifications are conducted based on statistically analyses of a first-hand data collection amongst 305 valid samples. This knowledge-based product recommendation system is one kind of an intelligent agent that is constructed base on ontology and rules that extracted from the empirical study. As the result, this study models customers’ decision-making behavior and translate it into the knowledge base of the product recommendation system to improve its search results. The system evaluation participated by 10 subjects with traveling and technical knowledge, and the result appears that the classification of information based on ontology can help user to understand the product more easily. Furthermore, the average satisfaction rate of information and recommendation of a travel website is 45%, and the rate of this system in the study is 85%. As the result, this study can improve the customers’ satisfaction significantily.
Книги з теми "Group Recommendation System"
Thorat, Sukhadeo, and R. P. Mamgain. Social group statistics and present statistical system : emerging policy issues, data needs and reforms: Recommendations for improvement in social group statistics. Edited by India. Ministry of Statistics and Programme Implementation and Indian Institute of Dalit Studies. New Delhi: Ministry of Statistics and Programme Implementation, Government of India and Indian Institute of Dalit Studies, 2012.
Знайти повний текст джерела46, SCOR Working Group. River inputs to ocean systems: Status and recommendations for research : final report of SCOR Working Group 46. Edited by Burton J. D. 1931-. Paris: Unesco, 1988.
Знайти повний текст джерелаWatts, A. G. Towards a PROSPECT (16-19) system?: A report for the Department of Education and Science of the trial of the PROSPECT (HE) system for use with the 16-19 age group in schools and colleges and of the recommendations of the expert group. London: National Council for Educational Technology, 1990.
Знайти повний текст джерелаTang, Man-Chung. The Story of the Koror Bridge. Zurich, Switzerland: International Association for Bridge and Structural Engineering (IABSE), 2014. http://dx.doi.org/10.2749/cs001.
Повний текст джерелаMigrating to euro: System strategies & best practices recommendations for the adaptation of information systems to the euro : report by the Euro Working Group. Brussels: European Commission, 1999.
Знайти повний текст джерелаNaji, Abdennasser. Total Quality Management in Education: Conditions for systemic improvement of the quality of learning outcomes. amazon, 2020. http://dx.doi.org/10.37870/979-8694752237.
Повний текст джерелаInstitute of Policy Studies (Islāmābād, Pakistan), ed. Tax system in Pakistan: A critical evaluation and recommendations for change : report of a working group, May/June 1986. Islamabad, Pakistan: Institute of Policy Studies, 1986.
Знайти повний текст джерелаGuideline for Preventive Chemotherapy for the Control of Taenia solium Taeniasis. Pan American Health Organization, 2021. http://dx.doi.org/10.37774/9789275123720.
Повний текст джерелаShanks, Trina R., Leslie Hollingsworth, and Patricia L. Miller. Building and Maintaining Community Capacity. Oxford University Press, 2017. http://dx.doi.org/10.1093/acprof:oso/9780190463311.003.0007.
Повний текст джерелаMasson, Isla, Lucy Baldwin, and Natalie Booth, eds. Critical Reflections on Women, Family, Crime and Justice. Bristol University Press, 2021. http://dx.doi.org/10.46692/9781447358701.
Повний текст джерелаЧастини книг з теми "Group Recommendation System"
Baatarjav, Enkh-Amgalan, Santi Phithakkitnukoon, and Ram Dantu. "Group Recommendation System for Facebook." In On the Move to Meaningful Internet Systems: OTM 2008 Workshops, 211–19. Berlin, Heidelberg: Springer Berlin Heidelberg, 2008. http://dx.doi.org/10.1007/978-3-540-88875-8_41.
Повний текст джерелаNtoutsi, Irene, Kostas Stefanidis, Kjetil Norvag, and Hans-Peter Kriegel. "gRecs: A Group Recommendation System Based on User Clustering." In Database Systems for Advanced Applications, 299–303. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-29035-0_25.
Повний текст джерелаRodríguez, Paula, Mauricio Giraldo, Valentina Tabares, Néstor Duque, and Demetrio Ovalle. "Recommendation System of Educational Resources for a Student Group." In Highlights of Practical Applications of Scalable Multi-Agent Systems. The PAAMS Collection, 419–27. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-39387-2_35.
Повний текст джерелаZuva, Tranos, and Keneilwe Zuva. "Virtual Group Movie Recommendation System Using Social Network Information." In Lecture Notes in Electrical Engineering, 325–36. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-33-4909-4_24.
Повний текст джерелаVillavicencio, Christian, Silvia Schiaffino, Jorge Andres Diaz-Pace, and Ariel Monteserin. "PUMAS-GR: A Negotiation-Based Group Recommendation System for Movies." In Advances in Practical Applications of Scalable Multi-agent Systems. The PAAMS Collection, 294–98. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-39324-7_34.
Повний текст джерелаPujahari, Abinash, Vineet Padmanabhan, and Soma Patel. "Nearest Neighbour with Priority Based Recommendation Approach to Group Recommender System." In Advances in Intelligent Systems and Computing, 347–54. New Delhi: Springer India, 2015. http://dx.doi.org/10.1007/978-81-322-2731-1_32.
Повний текст джерелаIrvan, Mhd, and Takao Terano. "Group Recommendation System for E-Learning Communities: A Multi-agent Approach." In Communications in Computer and Information Science, 35–46. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-52039-1_3.
Повний текст джерелаHuang, Hua-Hong, Sheng-Min Chiu, Yi-Chung Chen, and Chiang Lee. "Group Trip Recommendation Systems." In Advances in Intelligent Systems and Computing, 391–412. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-03402-3_27.
Повний текст джерелаSallam, Amer A., Siba K. Udgata, and Vineet Padmanabhan. "An Intelligent Recommendation System for Individual and Group of Mobile Marketplace Users Based on the Influence of Items’ Features among User Profile." In Communications in Computer and Information Science, 255–67. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-29219-4_30.
Повний текст джерелаMa, Wenkai, Gui Li, Zhengyu Li, Ziyang Han, and Keyan Cao. "A Tag-Based Group Recommendation Algorithm." In Web Information Systems and Applications, 677–83. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-30952-7_68.
Повний текст джерелаТези доповідей конференцій з теми "Group Recommendation System"
Su, Xue-Feng, Hua-Jun Zeng, and Zheng Chen. "Finding group shilling in recommendation system." In Special interest tracks and posters of the 14th international conference. New York, New York, USA: ACM Press, 2005. http://dx.doi.org/10.1145/1062745.1062818.
Повний текст джерелаKuei-Hong Lin, Yu-Shian Chiu, and Jia-Sin Chen. "An adaptive correlation-based group recommendation system." In 2011 International Symposium on Intelligent Signal Processing and Communications Systems (ISPACS 2011). IEEE, 2011. http://dx.doi.org/10.1109/ispacs.2011.6146060.
Повний текст джерелаOliveira, Amanda, and Frederico Durao. "A Group Recommendation Model Using Diversification Techniques." In Hawaii International Conference on System Sciences. Hawaii International Conference on System Sciences, 2021. http://dx.doi.org/10.24251/hicss.2021.326.
Повний текст джерелаKim, Noo-ri, and Jee-Hyong Lee. "Group recommendation system: Focusing on home group user in TV domain." In 2014 Joint 7th International Conference on Soft Computing and Intelligent Systems (SCIS) and 15th International Symposium on Advanced Intelligent Systems (ISIS). IEEE, 2014. http://dx.doi.org/10.1109/scis-isis.2014.7044866.
Повний текст джерелаLi, Hsin-Wei, Sok-Ian Sou, and Hsun-Ping Hsieh. "Room-based Playlist Arrangement System using Group Recommendation." In 2020 International Computer Symposium (ICS). IEEE, 2020. http://dx.doi.org/10.1109/ics51289.2020.00020.
Повний текст джерелаLiu, Xubo, Yuankai Ma, Yutian Feng, Huaixi Tang, and Zhitao Dai. "CGSPA: Comprehensive Group Similarity Preference Aggregation Algorithm for Group Itinerary Recommendation System." In 2019 IEEE 10th Annual Information Technology, Electronics and Mobile Communication Conference (IEMCON). IEEE, 2019. http://dx.doi.org/10.1109/iemcon.2019.8936245.
Повний текст джерелаYukawa, Masataka, Yugo Hayashi, Hitoshi Ogawa, and Victor V. Kryssanov. "A group recommendation system with a multi-modal user interface." In 2012 Joint 6th Intl. Conference on Soft Computing and Intelligent Systems (SCIS) and 13th Intl. Symposium on Advanced Intelligent Systems (ISIS). IEEE, 2012. http://dx.doi.org/10.1109/scis-isis.2012.6505391.
Повний текст джерелаMysore, Naveen. "An elastic group recommendation system designed for multivariate dynamic attributes." In 2016 IEEE/ACIS 15th International Conference on Computer and Information Science (ICIS). IEEE, 2016. http://dx.doi.org/10.1109/icis.2016.7550752.
Повний текст джерелаHan, Peng, Zhongxiao Li, Yong Liu, Peilin Zhao, Jing Li, Hao Wang, and Shuo Shang. "Contextualized Point-of-Interest Recommendation." In Twenty-Ninth International Joint Conference on Artificial Intelligence and Seventeenth Pacific Rim International Conference on Artificial Intelligence {IJCAI-PRICAI-20}. California: International Joint Conferences on Artificial Intelligence Organization, 2020. http://dx.doi.org/10.24963/ijcai.2020/344.
Повний текст джерелаPletneva, Olesya, Galina Yamaletdinova, and Marina Spirina. "Recommendation on Correction of Female Students Physical State of Special Medical Group." In The Public/Private in Modern Civilization, the 22nd Russian Scientific-Practical Conference (with international participation) (Yekaterinburg, April 16-17, 2020). Liberal Arts University – University for Humanities, Yekaterinburg, 2020. http://dx.doi.org/10.35853/ufh-public/private-2020-72.
Повний текст джерелаЗвіти організацій з теми "Group Recommendation System"
Caron, Patrick, Maureen Gitagia, Michael Hamm, Ulrich Hoffmann, Elizabeth Kimani-Murage, Tania Martínez-Cruz, Kathleen Merrigan, Patrick Roy Mooney, Nadia El-Hage Scialabba, and Tavseef Mairaj Shah. Blind Spots in the Agri-Food System Transformation Debate and Recommendations on How to Address These. TMG Research gGmbH, 2023. http://dx.doi.org/10.35435/1.2023.3.
Повний текст джерелаBarrett, Barbara, James Kimsey, Arnold Punaro, Dov Zakheim, Henry Dreifus, Kelly Van Niman, Lynne Schneider, and Stephan Smith. Military Postal Service Task Group. Recommendations Regarding the Military Postal System of the Department of Defense. Fort Belvoir, VA: Defense Technical Information Center, December 2005. http://dx.doi.org/10.21236/ada522673.
Повний текст джерелаDreifus, Henry, Denis Bovin, James Haveman, Herb Shear, William Winkenwerder, and Kelly S. Van Niman. Healthcare for Military Retirees Task Group. Recommendations Regarding Improvements to the Military Health Systems and Specifically Healthcare of Military Retirees. Fort Belvoir, VA: Defense Technical Information Center, December 2005. http://dx.doi.org/10.21236/ada522668.
Повний текст джерелаTabunov, I. A., T. N. Mikhalenko, L. D. Kuznetsova, A. V. Suetova, and M. A. Shilovskiy. METHODOLOGICAL RECOMMENDATIONS FOR WORKING WITH CHILDREN IN A SOCIALLY DANGEROUS SITUATION. Cherepovets State University, December 2022. http://dx.doi.org/10.12731/er0619.03122022.
Повний текст джерелаBourrier, Mathilde, Michael Deml, and Farnaz Mahdavian. Comparative report of the COVID-19 Pandemic Responses in Norway, Sweden, Germany, Switzerland and the United Kingdom. University of Stavanger, November 2022. http://dx.doi.org/10.31265/usps.254.
Повний текст джерелаPlumhans, Laure-Anne, Elke Dall, and Klaus Schuch. Study on Austrian actors, networks and activities in the field of science diplomacy. Bringing Austrian science diplomacy to the next step: Challenges, state of play and recommendations. ZSI - Centre for Social Innovation, September 2021. http://dx.doi.org/10.22163/fteval.2021.527.
Повний текст джерелаMarienko, Maiia V., Yulia H. Nosenko, and Mariya P. Shyshkina. Personalization of learning using adaptive technologies and augmented reality. [б. в.], November 2020. http://dx.doi.org/10.31812/123456789/4418.
Повний текст джерелаMintii, I. S. Using Learning Content Management System Moodle in Kryvyi Rih State Pedagogical University educational process. [б. в.], July 2020. http://dx.doi.org/10.31812/123456789/3866.
Повний текст джерелаFullan, Michael, and Joanne Quinn. How Do Disruptive Innovators Prepare Today's Students to Be Tomorrow's Workforce?: Deep Learning: Transforming Systems to Prepare Tomorrow’s Citizens. Inter-American Development Bank, December 2020. http://dx.doi.org/10.18235/0002959.
Повний текст джерелаTiefenthaler, Brigitte. Evaluierung der Nationalen Vernetzungsplattformen des BMBWF. Technopolis Group - Austria, February 2020. http://dx.doi.org/10.22163/fteval.2020.507.
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