{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T03:33:57Z","timestamp":1760240037511,"version":"build-2065373602"},"reference-count":44,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2019,2,21]],"date-time":"2019-02-21T00:00:00Z","timestamp":1550707200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Entropy"],"abstract":"<jats:p>This paper focuses on the problem of finding a particular data recommendation strategy based on the user preference and a system expected revenue. To this end, we formulate this problem as an optimization by designing the recommendation mechanism as close to the user behavior as possible with a certain revenue constraint. In fact, the optimal recommendation distribution is the one that is the closest to the utility distribution in the sense of relative entropy and satisfies expected revenue. We show that the optimal recommendation distribution follows the same form as the message importance measure (MIM) if the target revenue is reasonable, i.e., neither too small nor too large. Therefore, the optimal recommendation distribution can be regarded as the normalized MIM, where the parameter, called importance coefficient, presents the concern of the system and switches the attention of the system over data sets with different occurring probability. By adjusting the importance coefficient, our MIM based framework of data recommendation can then be applied to systems with various system requirements and data distributions. Therefore, the obtained results illustrate the physical meaning of MIM from the data recommendation perspective and validate the rationality of MIM in one aspect.<\/jats:p>","DOI":"10.3390\/e21020205","type":"journal-article","created":{"date-parts":[[2019,2,22]],"date-time":"2019-02-22T03:49:44Z","timestamp":1550807384000},"page":"205","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Matching Users\u2019 Preference under Target Revenue Constraints in Data Recommendation Systems"],"prefix":"10.3390","volume":"21","author":[{"given":"Shanyun","family":"Liu","sequence":"first","affiliation":[{"name":"Department of Electronic Engineering, Tsinghua University, Beijing 100084, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5282-4245","authenticated-orcid":false,"given":"Yunquan","family":"Dong","sequence":"additional","affiliation":[{"name":"School of Electronic and Information Engineering, Nanjing University of Information Science and Technology, Nanjing 210044, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0658-6079","authenticated-orcid":false,"given":"Pingyi","family":"Fan","sequence":"additional","affiliation":[{"name":"Department of Electronic Engineering, Tsinghua University, Beijing 100084, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Rui","family":"She","sequence":"additional","affiliation":[{"name":"Department of Electronic Engineering, Tsinghua University, Beijing 100084, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3350-3929","authenticated-orcid":false,"given":"Shuo","family":"Wan","sequence":"additional","affiliation":[{"name":"Department of Electronic Engineering, Tsinghua University, Beijing 100084, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2019,2,21]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Chen, M., Mao, S., Zhang, Y., and Leungm, V.C. (2014). Definition and features of big data. Big Data: Related Technologies, Challenges and Future Prospects, Springer.","DOI":"10.1007\/978-3-319-06245-7"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"190","DOI":"10.1109\/MCOM.2015.7295483","article-title":"Wireless communications in the era of big data","volume":"53","author":"Bi","year":"2015","journal-title":"IEEE Commun. Mag."},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Franklin, M., and Zdonik, S. (1998, January 1\u20134). Data in your face: Push technology in perspective. Proceedings of the 1998 ACM SIGMOD International Conference on Management of Data, Seattle, WA, USA.","DOI":"10.1145\/276304.276360"},{"key":"ref_4","unstructured":"Hauswirth, M. (2019, February 20). Internet-Scale Push Systems for Information Distribution\u2013Architecture, Components, and Communication. Available online: http:\/\/citeseerx.ist.psu.edu\/viewdoc\/download;jsessionid=2C5856A9798C3085378770287B32D626?doi=10.1.1.7.4907&rep=rep1&type=pdf."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"1917","DOI":"10.1109\/TNET.2014.2346694","article-title":"Proactive content download and user demand shaping for data networks","volume":"23","author":"Tadrous","year":"2015","journal-title":"IEEE Trans. Netw."},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Shoukry, O., ElMohsen, M.A., and Tadrous, J. (2014, January 10\u201314). Proactive scheduling for content pre-fetching in mobile networks. Proceedings of the 2014 IEEE International Conference on Communications, Sydney, Australia.","DOI":"10.1109\/ICC.2014.6883756"},{"key":"ref_7","unstructured":"Kim, Y., Lee, J., Park, S., and Choi, B. (2009, January 22\u201324). Mobile advertisement system using data push scheduling based on user preference. Proceedings of the IEEE Wireless Telecommunications Symposium (WTS), Prague, Czech Republic."},{"key":"ref_8","unstructured":"Podnar, I., Hauswirth, M., and Jazayeri, M. (2002, January 2\u20135). Mobile push: Delivering content to mobile users. Proceedings of the 22nd IEEE International Conference on Distributed Computing Systems Workshops, Vienna, Austria."},{"key":"ref_9","unstructured":"Nicopolitidis, P., Papadimitriou, G.I., and Pomportsis, A.S. (2005, January 18). An adaptive wireless push system for high-speed data broadcasting. Proceedings of the 14th IEEE Workshop on Local & Metropolitan Area Networks, Crete, Greece."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"652","DOI":"10.1109\/TC.2002.1009150","article-title":"Adaptive push-pull: Disseminating dynamic web data","volume":"51","author":"Bhide","year":"2002","journal-title":"IEEE Trans. Comput."},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Li, Y., Chen, L., Shi, H., Hong, X., and Shi, J. (2018). Joint content recommendation and delivery in mobile wireless Networks with Outage Management. Entropy, 20.","DOI":"10.3390\/e20010064"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"1586","DOI":"10.3390\/e16031586","article-title":"Optimal Forgery and Suppression of Ratings for Privacy Enhancement in Recommendation Systems","volume":"16","year":"2014","journal-title":"Entropy"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"2439","DOI":"10.1109\/TMM.2017.2701641","article-title":"personalized social image recommendation method based on user-image-tag model","volume":"19","author":"Zhang","year":"2017","journal-title":"IEEE Trans. Multimed."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"1217","DOI":"10.1109\/TMM.2016.2537216","article-title":"Differentially private online learning for cloud-based Video recommendation with multimedia big data in social networks","volume":"18","author":"Zhou","year":"2016","journal-title":"IEEE Trans. Multimed."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"318","DOI":"10.1109\/TLT.2012.11","article-title":"Context-aware recommender systems for learning: A survey and future challenges","volume":"5","author":"Verbert","year":"2012","journal-title":"IEEE Trans. Learn. Technol."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"13","DOI":"10.1145\/2846092","article-title":"On effective location-aware music recommendation","volume":"34","author":"Cheng","year":"2016","journal-title":"ACM Trans. Inf. Syst."},{"key":"ref_17","unstructured":"Elkan, C. (2001, January 4\u201310). The foundations of cost-sensitive learning. Proceedings of the Seventeenth International Joint Conference on Artificial Intelligence, Seattle, WA, USA."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"63","DOI":"10.1109\/TKDE.2006.17","article-title":"Training cost-sensitive neural networks with methods addressing the class imbalance problem","volume":"18","author":"Zhou","year":"2006","journal-title":"IEEE Trans. Knowl. Data Eng."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"16:1","DOI":"10.1145\/2431211.2431215","article-title":"A survey of cost-sensitive decision tree induction algorithms","volume":"45","author":"Lomax","year":"2013","journal-title":"ACM Comput. Surv."},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Du, J., Ni, E.A., and Ling, C.X. (2010, January 26\u201330). Adapting cost-sensitive learning for reject option. Proceedings of the 19th ACM International Conference on Information and Knowledge Management (CIKM), Toronto, ON, Canada.","DOI":"10.1145\/1871437.1871749"},{"key":"ref_21","first-page":"65","article-title":"Counterterrorism systems of spain and poland: Comparative studies","volume":"3","author":"Zieba","year":"2015","journal-title":"Prz. Politol."},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Ando, S., and Suzuki, E. (2006, January 18\u201322). An information theoretic approach to detection of minority subsets in database. Proceedings of the Sixth International Conference on Data Mining (ICDM), Hong Kong, China.","DOI":"10.1109\/ICDM.2006.19"},{"key":"ref_23","unstructured":"Jordan, M., Kleinberg, J., and Sch\u00f6lkopf, B. (2006). Estimation of Dependences Based on Empirical Data, Springer."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"714","DOI":"10.1109\/TITS.2015.2481928","article-title":"Information maximizing optimal sensor placement robust against variations of traffic demand based on importance of nodes","volume":"17","author":"Ivanchev","year":"2016","journal-title":"IEEE Trans. Intell. Transp. Syst."},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Kawanaka, T., Rokugawa, S., and Yamashita, H. (2017, January 10\u201313). Information security in communication network of memory channel considering information importance. Proceedings of the IEEE International Conference on Industrial Engineering and Engineering Management (IEEM), Singapore.","DOI":"10.1109\/IEEM.2017.8290076"},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"M\u00f6nks, U., and Lohweg, V. (2013, January 10\u201313). Machine conditioning by importance controlled information fusion. Proceedings of the IEEE 18th Conference on Emerging Technologies & Factory Automation (ETFA), Cagliari, Italy.","DOI":"10.1109\/ETFA.2013.6647984"},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Li, Y., Zhang, M., and Geng, X. (2015, January 14\u201317). Leveraging implicit relative labeling-importance information for effective multi-label learning. Proceedings of the IEEE International Conference on Data Mining (ICDM), Atlantic City, NJ, USA.","DOI":"10.1109\/ICDM.2015.41"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"600","DOI":"10.1109\/TIT.1967.1054054","article-title":"On linear unequal error protection codes","volume":"3","author":"Masnick","year":"1967","journal-title":"IEEE Trans. Inf. Theory"},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Fan, P., Dong, Y., Lu, J., and Liu, S. (2016, January 4\u20138). Message importance measure and its application to minority subset detection in big data. Proceedings of the IEEE Globecom Workshops (GC Wkshps), Washington, DC, USA.","DOI":"10.1109\/GLOCOMW.2016.7848960"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"623","DOI":"10.1002\/j.1538-7305.1948.tb00917.x","article-title":"A mathematical theory of communication","volume":"27","author":"Shannon","year":"1948","journal-title":"Bell Syst. Tech. J."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"2057","DOI":"10.1109\/18.720531","article-title":"Fifty years of shannon theory","volume":"44","author":"Verdu","year":"1998","journal-title":"IEEE Trans. Inf. Theory"},{"key":"ref_32","unstructured":"R\u00e9nyi, A. (July, January 20). On measures of entropy and information. Proceedings of the 4th Berkeley Symposium on Mathematical Statistics and Probability, Berkeley, CA, USA."},{"key":"ref_33","unstructured":"Fadeev, D.K. (1957). Zum Begriff der Entropie ciner endlichen Wahrscheinlichkeitsschemas. Arbeiten zur Informationstheorie I, Deutscher Verlag der Wissenschaften."},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"She, R., Liu, S., Dong, Y., and Fan, P. (2017, January 20\u201326). Focusing on a probability element: parameter selection of message importance measure in big data. Proceedings of the IEEE International Conference on Communications (ICC), Paris, France.","DOI":"10.1109\/ICC.2017.7996803"},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"5181","DOI":"10.1109\/TCOMM.2018.2847666","article-title":"Non-parametric Message Important Measure: Storage Code Design and Transmission Planning for Big Data","volume":"66","author":"Liu","year":"2018","journal-title":"IEEE Trans. Commun."},{"key":"ref_36","doi-asserted-by":"crossref","unstructured":"She, R., Liu, S., and Fan, P. (2018). Recognizing Information Feature Variation: Message Importance Transfer Measure and Its Applications in Big Data. Entropy, 20.","DOI":"10.3390\/e20060401"},{"key":"ref_37","doi-asserted-by":"crossref","unstructured":"Cover, T.M., and Thomas, J.A. (2006). Elements of Information Theory, Wiley. [2nd ed.].","DOI":"10.1002\/047174882X"},{"key":"ref_38","doi-asserted-by":"crossref","unstructured":"Liu, S., She, R., Wan, S., Fan, P., and Dong, Y. (2018, January 25\u201329). A Switch to the Concern of User: Importance Coefficient in Utility Distribution and Message Importance Measure. Proceedings of the IEEE International Wireless Communications & Mobile Computing Conference (IWCMC), Limassol, Cyprus.","DOI":"10.1109\/IWCMC.2018.8450338"},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"3797","DOI":"10.1109\/TIT.2014.2320500","article-title":"R\u00e9nyi divergence and kullback-leibler divergence","volume":"60","year":"2014","journal-title":"IEEE Trans. Inf. Theory"},{"key":"ref_40","unstructured":"She, R., Liu, S., and Fan, P. (arXiv, 2019). Information Measure Similarity Theory: Message Importance Measure via Shannon Entropy, arXiv."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"1431","DOI":"10.1109\/JSAC.2016.2545479","article-title":"Energy efficiency with proportional rate fairness in multirelay OFDM networks","volume":"34","author":"Xiong","year":"2016","journal-title":"IEEE J. Select. Areas Commun."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"3840","DOI":"10.1109\/TWC.2017.2689011","article-title":"Group cooperation with optimal resource allocation in wireless powered communication networks","volume":"16","author":"Xiong","year":"2017","journal-title":"IEEE Trans. Wirel. Commun."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"4564","DOI":"10.1109\/TVT.2010.2080695","article-title":"Delay-constrained optimal link scheduling in wireless sensor networks","volume":"59","author":"Wang","year":"2010","journal-title":"IEEE Trans. Veh. Technol."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"5775","DOI":"10.1109\/TVT.2015.2388483","article-title":"Optimal power allocation with delay constraint for signal transmission from a moving train to base stations in high-speed railway scenarios","volume":"64","author":"Zhang","year":"2015","journal-title":"IEEE Trans. Veh. Technol."}],"container-title":["Entropy"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1099-4300\/21\/2\/205\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T12:33:55Z","timestamp":1760186035000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1099-4300\/21\/2\/205"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,2,21]]},"references-count":44,"journal-issue":{"issue":"2","published-online":{"date-parts":[[2019,2]]}},"alternative-id":["e21020205"],"URL":"https:\/\/doi.org\/10.3390\/e21020205","relation":{},"ISSN":["1099-4300"],"issn-type":[{"type":"electronic","value":"1099-4300"}],"subject":[],"published":{"date-parts":[[2019,2,21]]}}}