{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T03:23:23Z","timestamp":1760239403280,"version":"build-2065373602"},"reference-count":48,"publisher":"MDPI AG","issue":"22","license":[{"start":{"date-parts":[[2020,11,10]],"date-time":"2020-11-10T00:00:00Z","timestamp":1604966400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>With the development of ocean exploration technology and the rapid growth in the amount of marine science observation data, people are faced with a great challenge to identify valuable data from the massive ocean observation data. A recommendation system is an effective method to improve retrieval capabilities to help users obtain valuable data. The two most popular recommendation algorithms are collaborative filtering algorithms and content-based filtering algorithms, which may not work well for marine science observation data given the complexity of data attributes and lack of user information. In this study, an approach was proposed based on data similarity and data correlation. Data similarity was calculated by analyzing the subject, source, spatial, and temporal attributes to obtain the recommendation list. Then, data correlation was calculated based on the literature on marine science data and ranking of the recommendation list to obtain the re-rank recommendation list. The approach was tested by simulated datasets collected from multiple marine data sharing websites, and the result suggested that the proposed method exhibits better effectiveness.<\/jats:p>","DOI":"10.3390\/s20226414","type":"journal-article","created":{"date-parts":[[2020,11,10]],"date-time":"2020-11-10T14:10:41Z","timestamp":1605017441000},"page":"6414","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":9,"title":["A Hybrid Recommendation System for Marine Science Observation Data Based on Content and Literature Filtering"],"prefix":"10.3390","volume":"20","author":[{"given":"Xiaoyang","family":"Song","sequence":"first","affiliation":[{"name":"State Key Laboratory of Acoustics, Institute of Acoustics, Chinese Academy of Sciences, Beijing 100190, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yonggang","family":"Guo","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Acoustics, Institute of Acoustics, Chinese Academy of Sciences, Beijing 100190, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yongguo","family":"Chang","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Acoustics, Institute of Acoustics, Chinese Academy of Sciences, Beijing 100190, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Fei","family":"Zhang","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Acoustics, Institute of Acoustics, Chinese Academy of Sciences, Beijing 100190, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Junfeng","family":"Tan","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Acoustics, Institute of Acoustics, Chinese Academy of Sciences, Beijing 100190, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jie","family":"Yang","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Acoustics, Institute of Acoustics, Chinese Academy of Sciences, Beijing 100190, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiaolong","family":"Shi","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Acoustics, Institute of Acoustics, Chinese Academy of Sciences, Beijing 100190, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2020,11,10]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Venkatesan, R., Tandon, A., Sengupta, D., and Navaneeth, K.N. (2018). Recent Trends in Ocean Observations, Springer.","DOI":"10.1007\/978-3-319-66493-4_1"},{"key":"ref_2","first-page":"21","article-title":"A review of the development and current situation of marine environment observation technology and instruments","volume":"32","author":"Qi","year":"2019","journal-title":"Shandong Sci."},{"key":"ref_3","first-page":"C12S01","article-title":"Introduction to special section: Coastal ocean observatories","volume":"109","author":"Schofield","year":"2004","journal-title":"J. Geophys. Res."},{"key":"ref_4","first-page":"1","article-title":"Satellite marine remote sensing in China","volume":"4892","author":"Pan","year":"2003","journal-title":"Proc. SPIE Int. Soc. Opt. Eng."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"648","DOI":"10.1093\/icesjms\/fss010","article-title":"Species identification in seamount fish aggregations using moored underwater video","volume":"69","author":"Peter","year":"2012","journal-title":"Ices J. Mar. Sci."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"12","DOI":"10.1016\/j.jmarsys.2013.09.010","article-title":"Underwater geophysical monitoring for European Multidisciplinary Seafloor and water column Observatories","volume":"130","author":"Monna","year":"2014","journal-title":"J. Mar. Syst."},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Xiao, C., Sun, D., Wang, S., Qiu, Z., Yu, H., and Zhang, J. (2018). Long-term changes in colored dissolved organic matter from satellite observations in the Bohai Sea and North Yellow Sea. Remote Sens., 10.","DOI":"10.3390\/rs10050688"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"1477","DOI":"10.1016\/j.dib.2018.06.020","article-title":"Experimental data on the air-sea energy fluxes at the tropical coastal ocean in the southern South China Sea","volume":"19","author":"Yusri","year":"2018","journal-title":"Data Brief"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"16","DOI":"10.5670\/oceanog.2018.121","article-title":"The Ocean Observatories Initiative","volume":"31","author":"Ulses","year":"2018","journal-title":"Oceanography"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"56","DOI":"10.1145\/245108.245121","article-title":"Recommender systems","volume":"40","author":"Resnick","year":"1997","journal-title":"Commun. ACM"},{"key":"ref_11","first-page":"3593","article-title":"User interest model construction and update for news recommendation","volume":"36","author":"Yuan","year":"2019","journal-title":"Appl. Res. Comput."},{"key":"ref_12","first-page":"32","article-title":"Design and implementation of music recommendation system based on android","volume":"35","author":"Bao","year":"2019","journal-title":"J. Shanxi Datong Univ."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"363","DOI":"10.1142\/S2196888819500192","article-title":"Improved movie recommendations based on a hybrid feature combination method","volume":"6","author":"Alshammari","year":"2019","journal-title":"Vietnam J. Comput. Sci."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"4155","DOI":"10.1007\/s11042-017-4542-z","article-title":"A content-based goods image recommendation system","volume":"77","author":"Yu","year":"2018","journal-title":"Multimed. Tools Appl."},{"key":"ref_15","first-page":"76","article-title":"Attribute clustering based collaborative filtering in patient prescription recommendation","volume":"118","author":"Zhang","year":"2016","journal-title":"Basic Clin. Pharmacol. Toxicol."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"83","DOI":"10.1023\/A:1013284820704","article-title":"Efficient adaptive-support association rule mining for recommender systems","volume":"6","author":"Lin","year":"2002","journal-title":"Data Min. Knowl. Discov."},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Kuang, L., Yu, L., Huang, L., Wang, Y., Ma, P., Li, C., and Zhu, Y. (2018). A Personalized QoS Prediction Approach for CPS Service Recommendation Based on Reputation and Location-Aware Collaborative Filtering. Sensors, 18.","DOI":"10.3390\/s18051556"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"890","DOI":"10.3390\/s18030890","article-title":"HyRA: A hybrid recommendation algorithm focused on smart POI. Ceut\u00ed as a study scenario","volume":"18","author":"Joanna","year":"2018","journal-title":"Sensors"},{"key":"ref_19","unstructured":"Ekstrand, M.D. (2007). Collaborative Filtering Recommender Systems, Springer."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"163","DOI":"10.1007\/s00530-017-0539-8","article-title":"A content-based recommendation algorithm for learning resources","volume":"24","author":"Shu","year":"2017","journal-title":"Multimed. Syst."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"404","DOI":"10.1016\/j.eswa.2017.08.008","article-title":"Content-based filtering for recommendation systems using multiattribute networks","volume":"89","author":"Son","year":"2017","journal-title":"Expert Syst. Appl."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"2821","DOI":"10.1177\/0040517518801200","article-title":"Examining collaborative filtering algorithms for clothing recommendation in e-commerce","volume":"89","author":"Hu","year":"2018","journal-title":"Text. Res. J."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"397","DOI":"10.1016\/j.ijinfomgt.2016.01.005","article-title":"Collaborative filtering with facial expressions for online video recommendation","volume":"36","author":"Choi","year":"2016","journal-title":"Int. J. Inf. Manag."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"48","DOI":"10.1016\/j.ins.2016.03.006","article-title":"Personalized recommendation of stories for commenting in forum-based social media","volume":"352\u2013353","author":"Bach","year":"2016","journal-title":"Inf. Sci."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"331","DOI":"10.1023\/A:1021240730564","article-title":"Hybrid recommender systems: Survey and experiments","volume":"12","author":"Burke","year":"2002","journal-title":"User Model. User Adapt. Interact."},{"key":"ref_26","first-page":"1","article-title":"Developing a contextually personalized hybrid recommender system","volume":"2018","author":"Bozanta","year":"2018","journal-title":"Mob. Infor. Syst."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"012101","DOI":"10.1088\/1742-6596\/1000\/1\/012101","article-title":"A hybrid approach using collaborative filtering and content based filtering for recommender system","volume":"1000","author":"Geetha","year":"2018","journal-title":"J. Phys. Conf."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/2842631","article-title":"STCAPLRS: A spatial-temporal context-aware personalized location recommendation system","volume":"7","author":"Fang","year":"2016","journal-title":"Acm Trans. Intell. Syst. Technol."},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Ceccaroni, L., Velickovski, F., Blaas, M., Wernand, M.R., and Subirats, L. (2018). Artificial intelligence and earth observation to explore water quality in the Wadden Sea. Earth Observation Open Science and Innovation, Springer.","DOI":"10.1007\/978-3-319-65633-5_18"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"471","DOI":"10.1016\/j.knosys.2008.03.005","article-title":"An empirical study on sea water quality prediction","volume":"21","author":"Hatzikos","year":"2008","journal-title":"Knowl. Based Syst."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"1023","DOI":"10.1080\/01431161.2016.1275056","article-title":"Mapping concentrations of surface water quality parameters using a novel remote sensing and artificial intelligence framework","volume":"38","author":"Din","year":"2017","journal-title":"Int. J. Remote Sens."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"645","DOI":"10.1007\/s13762-013-0378-x","article-title":"Prediction of water quality parameters of Karoon River (Iran) by artificial intelligence-based models","volume":"11","author":"Emamgholizadeh","year":"2014","journal-title":"Int. J. Environ. Sci. Technol."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"44924","DOI":"10.1109\/ACCESS.2020.2978078","article-title":"Artificial intelligence recommendation system of cancer rehabilitation scheme based on iot technology","volume":"8","author":"Han","year":"2020","journal-title":"IEEE Access"},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"9454","DOI":"10.1109\/ACCESS.2018.2789866","article-title":"A recommendation model based on deep neural network","volume":"6","author":"Zhang","year":"2018","journal-title":"IEEE Access"},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"413","DOI":"10.1016\/S0957-4174(03)00067-8","article-title":"The collaborative filtering recommendation based on SOM cluster-indexing CBR","volume":"25","author":"Roh","year":"2003","journal-title":"Expert Syst. Appl."},{"key":"ref_36","first-page":"23","article-title":"Making product recommendations more diverse","volume":"32","author":"Ziegler","year":"2010","journal-title":"Bull. Tech. Comm. Data Eng."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"143","DOI":"10.1145\/963770.963776","article-title":"Item-based top-N recommendation algorithms","volume":"22","author":"Deshpande","year":"2004","journal-title":"ACM Trans. Inf. Syst"},{"key":"ref_38","doi-asserted-by":"crossref","unstructured":"Peker, S., and Kocyigit, A. (2016, January 7\u201310). mRHR: A modified reciprocal hit rank metric for ranking evaluation of multiple preferences in top-n recommender systems. Proceedings of the International Conference on Artificial Intelligence: Methodology, Systems, and Applications, Varna, Bulgaria.","DOI":"10.1007\/978-3-319-44748-3_31"},{"key":"ref_39","doi-asserted-by":"crossref","unstructured":"Ziegler, C.N., Mcnee, S.M., Konstan, J.A., and Lausen, G. (2005, January 10\u201314). Improving Recommendation Lists through Topic Diversification. Proceedings of the International World Wide Web Conference Committee (IW3C2), Chiba, Japan.","DOI":"10.1145\/1060745.1060754"},{"key":"ref_40","doi-asserted-by":"crossref","unstructured":"Kennish, M.J. (2001). Practical Handbook of Marine Science, CRC Press.","DOI":"10.1201\/9781420038484"},{"key":"ref_41","unstructured":"Xian, T. (2005). The Research of Personalized Recommendation Methods Based on Item Rating Prediction and Classification. [Master\u2019s Thesis, Yanshan University]."},{"key":"ref_42","doi-asserted-by":"crossref","unstructured":"Liu, Y., Qiu, M., Liu, C., and Guo, Z. (2016, January 29\u201331). Big data in ocean observation: Opportunities and challenges. Proceedings of the 2nd International Conference on Big Data Computing and Communication (BigCom), Shenyang, China.","DOI":"10.1007\/978-3-319-42553-5_18"},{"key":"ref_43","unstructured":"Jige, G. (2007). Estimation and validation of surface currents in the global ocean from Argo floats. Insititute of Atmospheric Physics, Chinese Academy of Sciences."},{"key":"ref_44","first-page":"265","article-title":"Co-citation in the scientific literature: A new measure of the relationship between two documents","volume":"24","author":"Small","year":"2010","journal-title":"J. Assoc. Inf. Sci. Technol."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"1616","DOI":"10.1002\/asi.20335","article-title":"Co-occurrence matrices and their applications in information science: Extending ACA to the Web environment","volume":"57","author":"Leydesdorff","year":"2006","journal-title":"J. Am. Soc. Inf. Sci. Technol."},{"key":"ref_46","unstructured":"(2020, July 20). National Marine Data Center. Available online: http:\/\/mds.nmdis.org.cn\/."},{"key":"ref_47","unstructured":"(2020, July 20). China Argo Real-Time Data Center. Available online: http:\/\/www.argo.org.cn\/."},{"key":"ref_48","unstructured":"(2020, July 20). Seafloor Observation Network Experiment System. Available online: http:\/\/www.dns863.net\/oceanview\/index.html."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/20\/22\/6414\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T10:31:34Z","timestamp":1760178694000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/20\/22\/6414"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,11,10]]},"references-count":48,"journal-issue":{"issue":"22","published-online":{"date-parts":[[2020,11]]}},"alternative-id":["s20226414"],"URL":"https:\/\/doi.org\/10.3390\/s20226414","relation":{},"ISSN":["1424-8220"],"issn-type":[{"type":"electronic","value":"1424-8220"}],"subject":[],"published":{"date-parts":[[2020,11,10]]}}}