Zeitschriftenartikel zum Thema „Trust-based collaborative filtering“
Geben Sie eine Quelle nach APA, MLA, Chicago, Harvard und anderen Zitierweisen an
Machen Sie sich mit Top-50 Zeitschriftenartikel für die Forschung zum Thema "Trust-based collaborative filtering" bekannt.
Neben jedem Werk im Literaturverzeichnis ist die Option "Zur Bibliographie hinzufügen" verfügbar. Nutzen Sie sie, wird Ihre bibliographische Angabe des gewählten Werkes nach der nötigen Zitierweise (APA, MLA, Harvard, Chicago, Vancouver usw.) automatisch gestaltet.
Sie können auch den vollen Text der wissenschaftlichen Publikation im PDF-Format herunterladen und eine Online-Annotation der Arbeit lesen, wenn die relevanten Parameter in den Metadaten verfügbar sind.
Sehen Sie die Zeitschriftenartikel für verschiedene Spezialgebieten durch und erstellen Sie Ihre Bibliographie auf korrekte Weise.
Zeng, Yejia, und Zehui Qu. „Trust-Based Neural Collaborative Filtering“. Journal of Physics: Conference Series 1229 (Mai 2019): 012051. http://dx.doi.org/10.1088/1742-6596/1229/1/012051.
Der volle Inhalt der QuelleNgwawe, Edwin, Elisha Abade und Stephen Mburu. „Trust Enhanced Collaborative Filtering Recommendation Algorithm“. International Research Journal of Computer Science 10, Nr. 04 (31.05.2023): 88–96. http://dx.doi.org/10.26562/irjcs.2023.v1004.10.
Der volle Inhalt der QuelleKim, Hyoung Do. „Applying Consistency-Based Trust Definition to Collaborative Filtering“. KSII Transactions on Internet and Information Systems 3, Nr. 4 (30.08.2009): 366–75. http://dx.doi.org/10.3837/tiis.2009.04.002.
Der volle Inhalt der QuelleDuan, Miao. „Collaborative Filtering Recommendation Algorithm based on Trust Propagation“. International Journal of Security and Its Applications 9, Nr. 7 (31.07.2015): 99–108. http://dx.doi.org/10.14257/ijsia.2015.9.7.09.
Der volle Inhalt der QuelleGuo, Liangmin, Jiakun Liang, Ying Zhu, Yonglong Luo, Liping Sun und Xiaoyao Zheng. „Collaborative filtering recommendation based on trust and emotion“. Journal of Intelligent Information Systems 53, Nr. 1 (14.07.2018): 113–35. http://dx.doi.org/10.1007/s10844-018-0517-4.
Der volle Inhalt der QuelleFaridani, Vahid, Mehrdad Jalali und Majid Vafaei Jahan. „Collaborative filtering-based recommender systems by effective trust“. International Journal of Data Science and Analytics 3, Nr. 4 (15.03.2017): 297–307. http://dx.doi.org/10.1007/s41060-017-0049-y.
Der volle Inhalt der QuelleYuan, Zahir und Yang. „Modeling Implicit Trust in Matrix Factorization-Based Collaborative Filtering“. Applied Sciences 9, Nr. 20 (16.10.2019): 4378. http://dx.doi.org/10.3390/app9204378.
Der volle Inhalt der QuelleLiu, Duen-Ren, Chin-Hui Lai und Hsuan Chiu. „Sequence-based trust in collaborative filtering for document recommendation“. International Journal of Human-Computer Studies 69, Nr. 9 (August 2011): 587–601. http://dx.doi.org/10.1016/j.ijhcs.2011.06.001.
Der volle Inhalt der QuelleYeh, Tzu-Yu, und Rasha Kashef. „Trust-Based Collaborative Filtering Recommendation Systems on the Blockchain“. Advances in Internet of Things 10, Nr. 04 (2020): 37–56. http://dx.doi.org/10.4236/ait.2020.104004.
Der volle Inhalt der QuelleChen, Hailong, Haijiao Sun, Miao Cheng und Wuyue Yan. „A Recommendation Approach for Rating Prediction Based on User Interest and Trust Value“. Computational Intelligence and Neuroscience 2021 (06.03.2021): 1–9. http://dx.doi.org/10.1155/2021/6677920.
Der volle Inhalt der QuelleHuang, Wenjun, Junyu Chen und Yue Ding. „Research on Collaborative Filtering Recommendation Based on Trust Relationship and Rating Trust“. Frontiers in Business, Economics and Management 1, Nr. 2 (19.04.2021): 1–9. http://dx.doi.org/10.54097/fbem.v1i2.13.
Der volle Inhalt der QuelleSongjie Gong. „A Collaborative Filtering Recommendation Algorithm Based on Trust Network and Trust Factor“. Journal of Convergence Information Technology 8, Nr. 5 (15.03.2013): 1111–18. http://dx.doi.org/10.4156/jcit.vol8.issue5.129.
Der volle Inhalt der QuelleTan, Chengfang, Lin Cui und Xiaoyin Wu. „Fuzzy trust based collaborative filtering analysis for mobile user preferences“. Journal of Intelligent & Fuzzy Systems 40, Nr. 4 (12.04.2021): 8269–75. http://dx.doi.org/10.3233/jifs-189649.
Der volle Inhalt der QuelleMeng, Weizhi, Wenjuan Li und Lam For Kwok. „Towards Effective Trust-Based Packet Filtering in Collaborative Network Environments“. IEEE Transactions on Network and Service Management 14, Nr. 1 (März 2017): 233–45. http://dx.doi.org/10.1109/tnsm.2017.2664893.
Der volle Inhalt der QuelleSharma, Sanjeev Kumar, und Ugrasen Suman. „A trust-based architectural framework for collaborative filtering recommender system“. International Journal of Business Information Systems 16, Nr. 2 (2014): 134. http://dx.doi.org/10.1504/ijbis.2014.062835.
Der volle Inhalt der QuelleGou, Jin, Junjie Guo, Lu Zhang und Cheng Wang. „Collaborative filtering recommendation system based on trust-aware and domain experts“. Intelligent Data Analysis 23 (27.06.2019): 133–51. http://dx.doi.org/10.3233/ida-192531.
Der volle Inhalt der QuelleYe, Li, Chunming Wu und Min Li. „Collaborative Filtering Recommendation Based on Trust Model with Fused Similar Factor“. MATEC Web of Conferences 139 (2017): 00010. http://dx.doi.org/10.1051/matecconf/201713900010.
Der volle Inhalt der QuelleJiang, Liaoliang, Yuting Cheng, Li Yang, Jing Li, Hongyang Yan und Xiaoqin Wang. „A trust-based collaborative filtering algorithm for E-commerce recommendation system“. Journal of Ambient Intelligence and Humanized Computing 10, Nr. 8 (29.06.2018): 3023–34. http://dx.doi.org/10.1007/s12652-018-0928-7.
Der volle Inhalt der QuelleMa, Xiao, Hongwei Lu, Zaobin Gan und Jiangfeng Zeng. „An explicit trust and distrust clustering based collaborative filtering recommendation approach“. Electronic Commerce Research and Applications 25 (September 2017): 29–39. http://dx.doi.org/10.1016/j.elerap.2017.06.005.
Der volle Inhalt der QuelleParvin, Hashem, Parham Moradi und Shahrokh Esmaeili. „TCFACO: Trust-aware collaborative filtering method based on ant colony optimization“. Expert Systems with Applications 118 (März 2019): 152–68. http://dx.doi.org/10.1016/j.eswa.2018.09.045.
Der volle Inhalt der QuelleSong, Jiagang, Jiayu Song, Xinpan Yuan, Xiao He und Xinghui Zhu. „Graph Representation-Based Deep Multi-View Semantic Similarity Learning Model for Recommendation“. Future Internet 14, Nr. 2 (19.01.2022): 32. http://dx.doi.org/10.3390/fi14020032.
Der volle Inhalt der QuelleWu, Li Hua, und Wen Feng Chen. „Personalized Recommendation Based on Trust and Preference“. Applied Mechanics and Materials 713-715 (Januar 2015): 2288–91. http://dx.doi.org/10.4028/www.scientific.net/amm.713-715.2288.
Der volle Inhalt der QuelleHriekes, EEva Diab, und Yosser AlSayed Souleiman AlAtassi. „Improve the Performance of Advice Systems Based on Cooperative Liquidation Using Trust Relationships“. JOURNAL OF UNIVERSITY OF BABYLON for Pure and Applied Sciences 27, Nr. 1 (01.04.2019): 87–106. http://dx.doi.org/10.29196/jubpas.v27i1.2068.
Der volle Inhalt der QuelleZhang, Yao, Shuangliang Tai und Kunhui Ye. „Contractor Recommendation Model Using Credit Networking and Collaborative Filtering“. Buildings 12, Nr. 12 (22.11.2022): 2049. http://dx.doi.org/10.3390/buildings12122049.
Der volle Inhalt der QuelleZahir, Yuan und Moniz. „AgreeRelTrust—a Simple Implicit Trust Inference Model for Memory-Based Collaborative Filtering Recommendation Systems“. Electronics 8, Nr. 4 (11.04.2019): 427. http://dx.doi.org/10.3390/electronics8040427.
Der volle Inhalt der QuelleKim, Kyung Soo, Doo Soo Chang und Yong Suk Choi. „Boosting Memory-Based Collaborative Filtering Using Content-Metadata“. Symmetry 11, Nr. 4 (18.04.2019): 561. http://dx.doi.org/10.3390/sym11040561.
Der volle Inhalt der Quelle吴, 应良. „An Improved Collaborative Filtering Recommendation Model and Method Based on Social Trust“. E-Commerce Letters 08, Nr. 02 (2019): 63–73. http://dx.doi.org/10.12677/ecl.2018.82008.
Der volle Inhalt der QuelleMohammed Ismail, Dr, Dr K. Bhanu Prakash und Dr M. Nagabhushana Rao. „Collaborative filtering-based recommendation of online social voting“. International Journal of Engineering & Technology 7, Nr. 3 (16.07.2018): 1504. http://dx.doi.org/10.14419/ijet.v7i3.11630.
Der volle Inhalt der QuelleRoy, Falguni, und Mahamudul Hasan. „Comparative Analysis of Different Trust Metrics of User-User Trust-Based Recommendation System“. Computer Science 23, Nr. 3 (02.10.2022): 337–75. http://dx.doi.org/10.7494/csci.2022.23.3.4227.
Der volle Inhalt der QuelleMartinez-Pabon, Francisco, Juan Camilo Ospina-Quintero, Gustavo Ramirez-Gonzalez und Mario Munoz-Organero. „Recommending Ads from Trustworthy Relationships in Pervasive Environments“. Mobile Information Systems 2016 (2016): 1–18. http://dx.doi.org/10.1155/2016/8593173.
Der volle Inhalt der QuelleZuo, Long, Shuo Xiong, Xin Qi, Zheng Wen und Yiwen Tang. „Communication-Based Book Recommendation in Computational Social Systems“. Complexity 2021 (29.01.2021): 1–10. http://dx.doi.org/10.1155/2021/6651493.
Der volle Inhalt der QuelleZhimin Chen, Yi Jiang und Yao Zhao. „A Collaborative Filtering Recommendation Algorithm Based on User Interest Change and Trust Evaluation“. International Journal of Digital Content Technology and its Applications 4, Nr. 9 (31.12.2010): 106–13. http://dx.doi.org/10.4156/jdcta.vol4.issue9.13.
Der volle Inhalt der QuelleLai, Chin-Hui, Duen-Ren Liu und Cai-Sin Lin. „Novel personal and group-based trust models in collaborative filtering for document recommendation“. Information Sciences 239 (August 2013): 31–49. http://dx.doi.org/10.1016/j.ins.2013.03.030.
Der volle Inhalt der QuelleHe, Wei. „Interior Design Scheme Recommendation Method Based on Improved Collaborative Filtering Algorithm“. Wireless Communications and Mobile Computing 2021 (23.12.2021): 1–10. http://dx.doi.org/10.1155/2021/3834550.
Der volle Inhalt der QuelleChaomeng, Gao, und Wang Yonggang. „Analysis of Brand Visual Design Based on Collaborative Filtering Algorithm“. Discrete Dynamics in Nature and Society 2022 (13.01.2022): 1–8. http://dx.doi.org/10.1155/2022/8235966.
Der volle Inhalt der QuelleSobha Rani, K. „TrustSVD: A Novel Trust-Based Matrix Factorization Model with User Trust and Item Ratings“. International Journal of Advanced Research in Computer Science and Software Engineering 7, Nr. 11 (30.11.2017): 7. http://dx.doi.org/10.23956/ijarcsse.v7i11.422.
Der volle Inhalt der QuelleGhodousi, Elnaz, und Ali Hamzeh. „A New Approach for Trust Prediction by using collaborative filtering based of Pareto dominance in Social Networks“. Ciência e Natura 37 (19.12.2015): 95. http://dx.doi.org/10.5902/2179460x20758.
Der volle Inhalt der QuelleBanda, Latha, Karan Singh, Le Hoang Son, Mohamed Abdel-Basset, Pham Huy Thong, Hiep Xuan Huynh und David Taniar. „Recommender Systems Using Collaborative Tagging“. International Journal of Data Warehousing and Mining 16, Nr. 3 (Juli 2020): 183–200. http://dx.doi.org/10.4018/ijdwm.2020070110.
Der volle Inhalt der QuelleO'DONOVAN, JOHN, und BARRY SMYTH. „MINING TRUST VALUES FROM RECOMMENDATION ERRORS“. International Journal on Artificial Intelligence Tools 15, Nr. 06 (Dezember 2006): 945–62. http://dx.doi.org/10.1142/s0218213006003053.
Der volle Inhalt der QuellePaul, P. Mano, und R. Ravi. „A Collaborative Reputation-Based Vector Space Model for Email Spam Filtering“. Journal of Computational and Theoretical Nanoscience 15, Nr. 2 (01.02.2018): 474–79. http://dx.doi.org/10.1166/jctn.2018.7128.
Der volle Inhalt der QuelleChen, Chaochao, Xiaolin Zheng, Mengying Zhu und Litao Xiao. „Recommender System with Composite Social Trust Networks“. International Journal of Web Services Research 13, Nr. 2 (April 2016): 56–73. http://dx.doi.org/10.4018/ijwsr.2016040104.
Der volle Inhalt der QuelleF, Mary Harin Fernandez, Ramya S und Revathy V. „Social Recommendation Model with User Trust and Item Ratings Using Collaborative Filtering Technique in Hotel Application“. Informatica : Journal of Applied Machines Electrical Electronics Computer Science and Communication Systems 01, Nr. 01 (01.12.2020): 17–22. http://dx.doi.org/10.47812/ijamecs2010103.
Der volle Inhalt der QuelleVictor, Patricia, Chris Cornelis, Martine De Cock und Ankur Teredesai. „A Comparative Analysis of Trust-Enhanced Recommenders for Controversial Items“. Proceedings of the International AAAI Conference on Web and Social Media 3, Nr. 1 (20.03.2009): 342–45. http://dx.doi.org/10.1609/icwsm.v3i1.13986.
Der volle Inhalt der QuelleLai, Chin-Hui, und Yu-Chieh Chang. „Document recommendation based on the analysis of group trust and user weightings“. Journal of Information Science 45, Nr. 6 (04.01.2019): 845–62. http://dx.doi.org/10.1177/0165551518819973.
Der volle Inhalt der QuelleZhang, Shuai, Wenting Yang, Song Xu und Wenyu Zhang. „A Hybrid Social Network-based Collaborative Filtering Method for Personalized Manufacturing Service Recommendation“. International Journal of Computers Communications & Control 12, Nr. 5 (10.09.2017): 728. http://dx.doi.org/10.15837/ijccc.2017.5.2930.
Der volle Inhalt der QuelleHsu, Ping-Yu, Jui-Yi Chung und Yu-Chin Liu. „Using the beta distribution technique to detect attacked items from collaborative filtering“. Intelligent Data Analysis 25, Nr. 1 (26.01.2021): 121–37. http://dx.doi.org/10.3233/ida-194935.
Der volle Inhalt der QuelleXu, Chonghuan. „Personal Recommendation Using a Novel Collaborative Filtering Algorithm in Customer Relationship Management“. Discrete Dynamics in Nature and Society 2013 (2013): 1–9. http://dx.doi.org/10.1155/2013/739460.
Der volle Inhalt der QuelleZhang, Xuefeng, Xiuli Chen, Dewen Seng und Xujian Fang. „A Factored Similarity Model with Trust and Social Influence for Top-N Recommendation“. International Journal of Computers Communications & Control 14, Nr. 4 (05.08.2019): 590–607. http://dx.doi.org/10.15837/ijccc.2019.4.3577.
Der volle Inhalt der QuelleSun, Dasong, Shuqing Li, Wenjing Yan, Fusen Jiao und Junpeng Chen. „Research on User Interest Expression and Recommendation Service based on Three-dimensional Relationship of Users and Items“. International Journal on Recent and Innovation Trends in Computing and Communication 8, Nr. 5 (31.05.2020): 01–15. http://dx.doi.org/10.17762/ijritcc.v8i5.5382.
Der volle Inhalt der QuelleWu, Jian, Jiali Chang, Qingwei Cao und Changyong Liang. „A trust propagation and collaborative filtering based method for incomplete information in social network group decision making with type-2 linguistic trust“. Computers & Industrial Engineering 127 (Januar 2019): 853–64. http://dx.doi.org/10.1016/j.cie.2018.11.020.
Der volle Inhalt der Quelle