{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,2]],"date-time":"2026-06-02T23:10:12Z","timestamp":1780441812076,"version":"3.54.1"},"reference-count":35,"publisher":"Springer Science and Business Media LLC","issue":"2","license":[{"start":{"date-parts":[[2019,5,21]],"date-time":"2019-05-21T00:00:00Z","timestamp":1558396800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2019,5,21]],"date-time":"2019-05-21T00:00:00Z","timestamp":1558396800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"funder":[{"DOI":"10.13039\/501100001809","name":"Natural Science Foundation of China","doi-asserted-by":"crossref","award":["61672535, 61472005"],"award-info":[{"award-number":["61672535, 61472005"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100004761","name":"Natural Science Foundation of Hunan Province","doi-asserted-by":"crossref","award":["2019JJ20025, 2018JJ3203"],"award-info":[{"award-number":["2019JJ20025, 2018JJ3203"]}],"id":[{"id":"10.13039\/501100004761","id-type":"DOI","asserted-by":"crossref"}]},{"name":"Research Foundation of Education Bureau of Hunan Province","award":["17C0679"],"award-info":[{"award-number":["17C0679"]}]},{"name":"Hunan University of Science and Engineering Research Project","award":["17XKY071"],"award-info":[{"award-number":["17XKY071"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["World Wide Web"],"published-print":{"date-parts":[[2020,3]]},"DOI":"10.1007\/s11280-019-00693-x","type":"journal-article","created":{"date-parts":[[2019,5,22]],"date-time":"2019-05-22T02:52:24Z","timestamp":1558493544000},"page":"1319-1340","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":11,"title":["ICFR: An effective incremental collaborative filtering based recommendation architecture for personalized websites"],"prefix":"10.1007","volume":"23","author":[{"given":"Yayuan","family":"Tang","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kehua","family":"Guo","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ruifang","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tao","family":"Xu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jianhua","family":"Ma","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tao","family":"Chi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2019,5,21]]},"reference":[{"issue":"3","key":"693_CR1","doi-asserted-by":"publisher","first-page":"359","DOI":"10.1007\/s13278-012-0083-7","volume":"3","author":"V Agarwal","year":"2013","unstructured":"Agarwal, V., Bharadwaj, K.K.: A collaborative filtering framework for friends recommendation in social networks based on interaction intensity and adaptive user similarity[J]. Soc. Netw. Anal. Min. 3(3), 359\u2013379 (2013)","journal-title":"Soc. Netw. Anal. Min."},{"key":"693_CR2","doi-asserted-by":"crossref","unstructured":"Aggarwal C C. Content-based recommender systems[M]\/\/recommender systems. Springer International Publishing: 139\u2013166 (2016)","DOI":"10.1007\/978-3-319-29659-3_4"},{"key":"693_CR3","doi-asserted-by":"crossref","unstructured":"Aggarwal C C. Model-based collaborative filtering[M]\/\/recommender systems. Springer International Publishing: 71\u2013138 (2016)","DOI":"10.1007\/978-3-319-29659-3_3"},{"issue":"2","key":"693_CR4","first-page":"12","volume":"8","author":"A Bellog\u00edn","year":"2014","unstructured":"Bellog\u00edn, A., Castells, P., Cantador, I.: Neighbor selection and weighting in user-based collaborative filtering: a performance prediction approach[J]. ACM Transactions on the Web (TWEB). 8(2), 12 (2014)","journal-title":"ACM Transactions on the Web (TWEB)"},{"key":"693_CR5","first-page":"1","volume-title":"Pearson Correlation Coefficient[M]\/\/Noise Reduction in Speech Processing","author":"J Benesty","year":"2009","unstructured":"Benesty, J., Chen, J., Huang, Y., et al.: Pearson Correlation Coefficient[M]\/\/Noise Reduction in Speech Processing, pp. 1\u20134. Springer, Berlin Heidelberg (2009)"},{"key":"693_CR6","doi-asserted-by":"crossref","unstructured":"Chang A D, Liao J F, Chang P C, et al.: Application of artificial immune systems combines collaborative filtering in movie recommendation system[C]\/\/computer supported cooperative work in design (CSCWD), proceedings of the 2014 IEEE 18th international conference on. IEEE 277\u2013282 (2014)","DOI":"10.1109\/CSCWD.2014.6846855"},{"key":"693_CR7","doi-asserted-by":"crossref","unstructured":"Chen X, Xia M, Cheng J, et al.: Trend prediction of internet public opinion based on collaborative filtering[C]\/\/natural computation, fuzzy systems and knowledge discovery (ICNC-FSKD), 2016 12th international conference on. IEEE, 2016: 583\u2013588 (2016)","DOI":"10.1109\/FSKD.2016.7603238"},{"key":"693_CR8","doi-asserted-by":"crossref","unstructured":"de Gemmis M, Lops P, Musto C, et al.: Semantics-aware content-based recommender systems[M]\/\/recommender systems handbook. Springer US: 119\u2013159 (2015)","DOI":"10.1007\/978-1-4899-7637-6_4"},{"key":"693_CR9","doi-asserted-by":"crossref","unstructured":"Elahi M, Ricci F, Rubens N. Active learning in collaborative filtering recommender systems[C]\/\/international conference on electronic commerce and web technologies. Springer International Publishing: 113\u2013124 (2014)","DOI":"10.1007\/978-3-319-10491-1_12"},{"issue":"2\u20133","key":"693_CR10","doi-asserted-by":"publisher","first-page":"221","DOI":"10.1007\/s11257-016-9172-z","volume":"26","author":"I Fern\u00e1ndez-Tob\u00edas","year":"2016","unstructured":"Fern\u00e1ndez-Tob\u00edas, I., Braunhofer, M., Elahi, M., et al.: Alleviating the new user problem in collaborative filtering by exploiting personality information[J]. User Model. User-Adap. Inter. 26(2\u20133), 221\u2013255 (2016)","journal-title":"User Model. User-Adap. Inter."},{"key":"693_CR11","unstructured":"George T, Merugu S. A scalable collaborative filtering framework based on co-clustering[C]\/\/Data Mining, Fifth IEEE international conference on. IEEE, 2005: 4 pp."},{"key":"693_CR12","doi-asserted-by":"publisher","first-page":"24239","DOI":"10.1109\/ACCESS.2018.2828081","volume":"6","author":"Yayuan Tang","year":"2018","unstructured":"Tang Y., Wang H., Guo K., et al. Relevant Feedback Based Accurate and Intelligent Retrieval on Capturing User Intention for Personalized Websites[J]. IEEE Access. 6, 24239\u201324248 (2018)","journal-title":"IEEE Access"},{"key":"693_CR13","doi-asserted-by":"crossref","unstructured":"Hasan M, Ahmed S, Malik M A I, et al.: A comprehensive approach towards user-based collaborative filtering recommender system[C]\/\/computational intelligence (IWCI), international workshop on. IEEE: 159\u2013164 (2016)","DOI":"10.1109\/IWCI.2016.7860358"},{"key":"693_CR14","doi-asserted-by":"crossref","unstructured":"Herlocker J L, Konstan J A, Borchers A, et al.: An algorithmic framework for performing collaborative filtering[C]\/\/proceedings of the 22nd annual international ACM SIGIR conference on research and development in information retrieval. ACM: 230\u2013237 (1999)","DOI":"10.1145\/312624.312682"},{"key":"693_CR15","doi-asserted-by":"crossref","unstructured":"Jamali M, Ester M.: Trustwalker: a random walk model for combining trust-based and item-based recommendation[C]\/\/proceedings of the 15th ACM SIGKDD international conference on knowledge discovery and data mining. ACM: 397\u2013406 (2009)","DOI":"10.1145\/1557019.1557067"},{"issue":"1","key":"693_CR16","doi-asserted-by":"publisher","first-page":"11","DOI":"10.4304\/jsw.8.1.11-18","volume":"8","author":"D Jia","year":"2013","unstructured":"Jia, D., Zhang, F., Liu, S.: A robust collaborative filtering recommendation algorithm based on multidimensional trust model[J]. JSW. 8(1), 11\u201318 (2013)","journal-title":"JSW"},{"key":"693_CR17","doi-asserted-by":"crossref","unstructured":"Jia Z, Yang Y, Gao W, et al. User-based collaborative filtering for tourist attraction recommendations[C]\/\/Computational Intelligence & Communication Technology (CICT), 2015 IEEE international conference on. IEEE: 22\u201325 (2015)","DOI":"10.1109\/CICT.2015.20"},{"issue":"3","key":"693_CR18","doi-asserted-by":"publisher","first-page":"357","DOI":"10.1007\/s10791-006-4651-1","volume":"9","author":"R Jin","year":"2006","unstructured":"Jin, R., Si, L., Zhai, C.: A study of mixture models for collaborative filtering[J]. Inf. Retr. 9(3), 357\u2013382 (2006)","journal-title":"Inf. Retr."},{"issue":"1","key":"693_CR19","doi-asserted-by":"publisher","first-page":"146","DOI":"10.1109\/MNET.2018.1700154","volume":"32","author":"Kehua Guo","year":"2018","unstructured":"Guo K., Liang Z., Shi R., et al. Transparent learning: An incremental machine learning framework based on transparent computing[J]. IEEE Network. 32(1),146-151 (2018)","journal-title":"IEEE Network"},{"key":"693_CR20","doi-asserted-by":"crossref","unstructured":"Li J, Wang Y, Wu J, et al.: Application of User-Based Collaborative Filtering Recommendation Technology on Logistics Platform[C]\/\/Business Intelligence and Financial Engineering (BIFE), 2013 Sixth international conference on. IEEE: 135\u2013138 (2013)","DOI":"10.1109\/BIFE.2013.30"},{"key":"693_CR21","unstructured":"Li W, Xu H, Ji M, et al.: A hierarchy weighting similarity measure to improve user-based collaborative filtering algorithm[C]\/\/computer and communications (ICCC), 2016 2nd IEEE international conference on. IEEE, 2016: 843\u2013846 (2016)"},{"key":"693_CR22","doi-asserted-by":"publisher","first-page":"273","DOI":"10.1016\/j.physa.2017.04.041","volume":"483","author":"Wenping Ma","year":"2017","unstructured":"Ma W, Ren C, Wu Y, et al. Personalized recommendation via unbalance full-connectivity inference[J]. Physica A: Statistical Mechanics and its Applications, 2017, 483: 273\u2013279","journal-title":"Physica A: Statistical Mechanics and its Applications"},{"key":"693_CR23","doi-asserted-by":"crossref","unstructured":"Meehan K, Lunney T, Curran K, et al.: Context-aware intelligent recommendation system for tourism[C]\/\/pervasive computing and communications workshops (PERCOM workshops), 2013 IEEE international conference on. IEEE 328\u2013331 (2013)","DOI":"10.1109\/PerComW.2013.6529508"},{"key":"693_CR24","unstructured":"Papagelis M, Rousidis I, Plexousakis D, et al. Incremental collaborative filtering for highly-scalable recommendation algorithms[C]\/\/International Symposium on Methodologies for Intelligent \u2018"},{"key":"693_CR25","doi-asserted-by":"publisher","first-page":"455","DOI":"10.1016\/j.jocs.2017.02.005","volume":"28","author":"Kehua Guo","year":"2018","unstructured":"Guo K., Liang Z., Tang Y., et al. SOR: An optimized semantic ontology retrieval algorithm for heterogeneous multimedia big data[J]. Journal of computational science. 28, 455- 465 (2018)","journal-title":"Journal of Computational Science"},{"key":"693_CR26","doi-asserted-by":"crossref","unstructured":"Sarwar, B., Karypis, G., Konstan, J., et al.: Item-based collaborative filtering recommendation algorithms[C]\/\/proceedings of the 10th international conference on world wide web. ACM. 285\u2013295 (2001)","DOI":"10.1145\/371920.372071"},{"key":"693_CR27","doi-asserted-by":"crossref","unstructured":"Shardanand U, Maes P.: Social information filtering: algorithms for automating \u201cword of mouth\u201d[C]\/\/proceedings of the SIGCHI conference on human factors in computing systems. ACM Press\/Addison-Wesley Publishing Co.: 210\u2013217 (1995)","DOI":"10.1145\/223904.223931"},{"key":"693_CR28","doi-asserted-by":"crossref","unstructured":"Veena C, Babu B V. A User-Based Recommendation with a Scalable Machine Learning Tool[J]. International Journal of Electrical and Computer Engineering, 2015, 5(5)","DOI":"10.11591\/ijece.v5i5.pp1153-1157"},{"key":"693_CR29","doi-asserted-by":"crossref","unstructured":"Wang Y, Feng D, Li D, et al.: A mobile recommendation system based on logistic regression and gradient boosting decision trees[C]\/\/neural networks (IJCNN), 2016 international joint conference on. IEEE: 1896\u20131902 (2016)","DOI":"10.1109\/IJCNN.2016.7727431"},{"key":"693_CR30","doi-asserted-by":"publisher","first-page":"452","DOI":"10.1016\/j.future.2016.08.004","volume":"76","author":"J Wang","year":"2017","unstructured":"Wang, J., Cao, Y., Li, B., et al.: Particle swarm optimization based clustering algorithm with mobile sink for WSNs[J]. Futur. Gener. Comput. Syst. 76, 452\u2013457 (2017)","journal-title":"Futur. Gener. Comput. Syst."},{"issue":"7","key":"693_CR31","doi-asserted-by":"publisher","first-page":"3277","DOI":"10.1007\/s11227-016-1947-9","volume":"73","author":"J Wang","year":"2017","unstructured":"Wang, J., Cao, J., Ji, S., et al.: Energy-efficient cluster-based dynamic routes adjustment approach for wireless sensor networks with mobile sinks[J]. J. Supercomput. 73(7), 3277\u20133290 (2017)","journal-title":"J. Supercomput."},{"key":"693_CR32","doi-asserted-by":"publisher","first-page":"66","DOI":"10.1016\/j.physa.2013.11.013","volume":"396","author":"J Zhang","year":"2014","unstructured":"Zhang, J., Peng, Q., Sun, S., et al.: Collaborative filtering recommendation algorithm based on user preference derived from item domain features[J]. Physica A: Statistical Mechanics and its Applications. 396, 66\u201376 (2014)","journal-title":"Physica A: Statistical Mechanics and its Applications"},{"key":"693_CR33","unstructured":"Zhao Z D, Shang M S. User-based collaborative-filtering recommendation algorithms on hadoop[C]\/\/Knowledge Discovery and Data Mining, 2010. WKDD'10.Third International Conference on. IEEE: 478\u2013481 (2010)"},{"issue":"6","key":"693_CR34","doi-asserted-by":"publisher","first-page":"559","DOI":"10.1109\/THMS.2017.2725341","volume":"48","author":"X Zhou","year":"2018","unstructured":"Zhou, X., Wu, B., Jin, Q.: Analysis of user network and correlation for community discovery based on topic-aware similarity and behavioral influence[J]. IEEE Transactions on Human-Machine Systems. 48(6), 559\u2013571 (2018)","journal-title":"IEEE Transactions on Human-Machine Systems"},{"key":"693_CR35","doi-asserted-by":"crossref","unstructured":"Zhou X, Liang W, Kevin I, et al.: Academic Influence Aware and Multidimensional Network Analysis for Research Collaboration Navigation Based on Scholarly Big Data[J]. IEEE Transactions on Emerging Topics in Computing, (2018)","DOI":"10.1109\/TETC.2018.2860051"}],"container-title":["World Wide Web"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s11280-019-00693-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s11280-019-00693-x\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s11280-019-00693-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2020,5,19]],"date-time":"2020-05-19T23:31:28Z","timestamp":1589931088000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s11280-019-00693-x"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,5,21]]},"references-count":35,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2020,3]]}},"alternative-id":["693"],"URL":"https:\/\/doi.org\/10.1007\/s11280-019-00693-x","relation":{},"ISSN":["1386-145X","1573-1413"],"issn-type":[{"value":"1386-145X","type":"print"},{"value":"1573-1413","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019,5,21]]},"assertion":[{"value":"10 August 2018","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"4 April 2019","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"6 May 2019","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"21 May 2019","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}