{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,9]],"date-time":"2026-10-09T01:33:57Z","timestamp":1791509637067,"version":"4.3.4"},"reference-count":124,"publisher":"Springer Science and Business Media LLC","issue":"6","license":[{"start":{"date-parts":[[2022,5,13]],"date-time":"2022-05-13T00:00:00Z","timestamp":1652400000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2022,5,13]],"date-time":"2022-05-13T00:00:00Z","timestamp":1652400000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"funder":[{"name":"NSERC Discovery Grant program","award":["3"],"award-info":[{"award-number":["3"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Knowl Inf Syst"],"published-print":{"date-parts":[[2022,6]]},"DOI":"10.1007\/s10115-022-01679-4","type":"journal-article","created":{"date-parts":[[2022,5,13]],"date-time":"2022-05-13T04:03:49Z","timestamp":1652414629000},"page":"1417-1455","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":52,"title":["Data pricing in machine learning pipelines"],"prefix":"10.1007","volume":"64","author":[{"given":"Zicun","family":"Cong","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xuan","family":"Luo","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2200-8711","authenticated-orcid":false,"given":"Jian","family":"Pei","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Feida","family":"Zhu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yong","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2022,5,13]]},"reference":[{"key":"1679_CR1","doi-asserted-by":"publisher","unstructured":"Agarwal A, Dahleh MA, Sarkar T (2019) A marketplace for data: an algorithmic solution. In: Karlin A, Immorlica N, Johari R (eds) Proceedings of the 2019 ACM conference on economics and computation, EC 2019, Phoenix, AZ, USA, June 24\u201328, 2019. ACM, pp 701\u2013726. https:\/\/doi.org\/10.1145\/3328526.3329589","DOI":"10.1145\/3328526.3329589"},{"key":"1679_CR2","unstructured":"Appen (2022) Appen. https:\/\/appen.com. Accessed 04 Jan 2022"},{"issue":"1","key":"1679_CR3","doi-asserted-by":"publisher","first-page":"121","DOI":"10.4086\/toc.2012.v008a006","volume":"8","author":"S Arora","year":"2012","unstructured":"Arora S, Hazan E, Kale S (2012) The multiplicative weights update method: a meta-algorithm and applications. Theory Comput 8(1):121\u2013164. https:\/\/doi.org\/10.4086\/toc.2012.v008a006","journal-title":"Theory Comput"},{"key":"1679_CR4","first-page":"22","volume":"17","author":"LM Ausubel","year":"2006","unstructured":"Ausubel LM, Milgrom P et al (2006) The lovely but lonely Vickrey auction. Comb Auctions 17:22\u201326","journal-title":"Comb Auctions"},{"issue":"2","key":"1679_CR5","doi-asserted-by":"publisher","first-page":"218","DOI":"10.1287\/mksc.2014.0894","volume":"34","author":"S Balasubramanian","year":"2015","unstructured":"Balasubramanian S, Bhattacharya S, Krishnan VV (2015) Pricing information goods: a strategic analysis of the selling and pay-per-use mechanisms. Mark Sci 34(2):218\u2013234","journal-title":"Mark Sci"},{"key":"1679_CR6","unstructured":"BDEX (2021) Bdex. https:\/\/www.bdex.com. Accessed 09 May 2021"},{"key":"1679_CR7","unstructured":"Brendan M, Daniel R (2017) Federated learning: collaborative machine learning without centralized training data. Google AI Blog. https:\/\/ai.googleblog.com\/2017\/04\/federated-learning-collaborative.html. Accessed 02 Jul 2021"},{"key":"1679_CR8","doi-asserted-by":"publisher","DOI":"10.4135\/9781446276518","volume-title":"Business-to-business marketing","author":"R Brennan","year":"2013","unstructured":"Brennan R, Canning L, Mcdowell R (2013) Business-to-business marketing. Sage Publications, Thousand Oaks. https:\/\/doi.org\/10.4135\/9781446276518"},{"key":"1679_CR9","unstructured":"Brown TB, Mann B, Ryder N, Subbiah M, Kaplan J, Dhariwal P, Neelakantan A, Shyam P, Sastry G, Askell A, Agarwal S, Herbert-Voss A, Krueger G, Henighan T, Child R, Ramesh A, Ziegler DM, Wu J, Winter C, Hesse C, Chen M, Sigler E, Litwin M, Gray S, Chess B, Clark J, Berner C, McCandlish S, Radford A, Sutskever I, Amodei D (2020) Language models are few-shot learners. In: Larochelle H, Ranzato M, Hadsell R, Balcan M, Lin H (eds) Advances in neural information processing systems 33: annual conference on neural information processing systems 2020, NeurIPS 2020, December 6\u201312, 2020, virtual. https:\/\/proceedings.neurips.cc\/paper\/2020\/hash\/1457c0d6bfcb4967418bfb8ac142f64a-Abstract.html"},{"key":"1679_CR10","doi-asserted-by":"publisher","unstructured":"Buneman P, Tan WC (2007) Provenance in databases. In: Chan CY, Ooi BC, Zhou A (eds) Proceedings of the ACM SIGMOD international conference on management of data, Beijing, China, June 12\u201314, 2007. ACM, pp 1171\u20131173. https:\/\/doi.org\/10.1145\/1247480.1247646","DOI":"10.1145\/1247480.1247646"},{"key":"1679_CR11","doi-asserted-by":"publisher","DOI":"10.1093\/acprof:oso\/9780195189629.001.0001","volume-title":"Microeconomics: optimization, experiments, and behavior. OUP Catalogue","author":"JP Burkett","year":"2006","unstructured":"Burkett JP (2006) Microeconomics: optimization, experiments, and behavior. OUP Catalogue. Oxford University Press, New York"},{"issue":"1","key":"1679_CR12","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1080\/03610927408827101","volume":"3","author":"T Cali\u0144ski","year":"1974","unstructured":"Cali\u0144ski T, Harabasz J (1974) A dendrite method for cluster analysis. Commun Stat Theory Methods 3(1):1\u201327","journal-title":"Commun Stat Theory Methods"},{"key":"1679_CR13","unstructured":"Caruso (2022) Caruso dataplace. https:\/\/www.caruso-dataplace.com\/pricing\/. Accessed 04 Jan 2022"},{"key":"1679_CR14","doi-asserted-by":"publisher","DOI":"10.2200\/S00355ED1V01Y201107AIM016","volume-title":"Computational aspects of cooperative game theory. Synthesis lectures on artificial intelligence and machine learning","author":"G Chalkiadakis","year":"2011","unstructured":"Chalkiadakis G, Elkind E, Wooldridge MJ (2011) Computational aspects of cooperative game theory. Synthesis lectures on artificial intelligence and machine learning. Morgan & Claypool Publishers, San Rafael. https:\/\/doi.org\/10.2200\/S00355ED1V01Y201107AIM016"},{"key":"1679_CR15","first-page":"1069","volume":"12","author":"K Chaudhuri","year":"2011","unstructured":"Chaudhuri K, Monteleoni C, Sarwate AD (2011) Differentially private empirical risk minimization. J Mach Learn Res 12:1069\u20131109","journal-title":"J Mach Learn Res"},{"issue":"1","key":"1679_CR16","doi-asserted-by":"publisher","first-page":"1","DOI":"10.14778\/3357377.3357378","volume":"13","author":"S Chawla","year":"2019","unstructured":"Chawla S, Deep S, Koutris P, Teng Y (2019) Revenue maximization for query pricing. Proc VLDB Endow 13(1):1\u201314. https:\/\/doi.org\/10.14778\/3357377.3357378","journal-title":"Proc VLDB Endow"},{"key":"1679_CR17","doi-asserted-by":"publisher","unstructured":"Chen L, Koutris P, Kumar A (2019) Towards model-based pricing for machine learning in a data marketplace. In: Boncz PA, Manegold S, Ailamaki A, Deshpande A, Kraska T (eds) Proceedings of the 2019 international conference on management of data, SIGMOD conference 2019, Amsterdam, The Netherlands, June 30\u2013July 5, 2019. ACM, pp 1535\u20131552. https:\/\/doi.org\/10.1145\/3299869.3300078","DOI":"10.1145\/3299869.3300078"},{"key":"1679_CR18","unstructured":"Chen L, Zaharia M, Zou JY (2020) Frugalml: How to use ML prediction APIs more accurately and cheaply. In: Advances in neural information processing systems, vol 33"},{"key":"1679_CR19","unstructured":"Cloud G (2022) Google cloud. https:\/\/cloud.google.com\/products\/ai. Accessed 04 Jan 2022"},{"issue":"4","key":"1679_CR20","doi-asserted-by":"publisher","first-page":"495","DOI":"10.1080\/00401706.1980.10486199","volume":"22","author":"RD Cook","year":"1980","unstructured":"Cook RD, Weisberg S (1980) Characterizations of an empirical influence function for detecting influential cases in regression. Technometrics 22(4):495\u2013508. https:\/\/doi.org\/10.1080\/00401706.1980.10486199","journal-title":"Technometrics"},{"key":"1679_CR21","doi-asserted-by":"publisher","unstructured":"Dandekar P, Fawaz N, Ioannidis S (2012) Privacy auctions for recommender systems. In: Goldberg PW (ed) Internet and network economics\u20148th international workshop, WINE 2012, Liverpool, UK, December 10\u201312, 2012. Proceedings, lecture notes in computer science, vol 7695. Springer, pp 309\u2013322. https:\/\/doi.org\/10.1007\/978-3-642-35311-6_23","DOI":"10.1007\/978-3-642-35311-6_23"},{"key":"1679_CR22","doi-asserted-by":"publisher","unstructured":"Dasgupta A, Ghosh A (2013) Crowdsourced judgement elicitation with endogenous proficiency. In: Schwabe D, Almeida VAF, Glaser H, Baeza-Yates R, Moon SB (eds) 22nd International world wide web conference, WWW \u201913, Rio de Janeiro, Brazil, May 13\u201317, 2013. International World Wide Web Conferences Steering Committee\/ACM, pp 319\u2013330. https:\/\/doi.org\/10.1145\/2488388.2488417","DOI":"10.1145\/2488388.2488417"},{"key":"1679_CR23","doi-asserted-by":"publisher","unstructured":"Datar M, Immorlica N, Indyk P, Mirrokni VS (2004) Locality-sensitive hashing scheme based on p-stable distributions. In: Snoeyink J, Boissonnat J (eds) Proceedings of the 20th ACM symposium on computational geometry, Brooklyn, New York, USA, June 8\u201311, 2004. ACM, pp 253\u2013262. https:\/\/doi.org\/10.1145\/997817.997857","DOI":"10.1145\/997817.997857"},{"key":"1679_CR24","unstructured":"Datarade (2022) Datarade data marketplace. https:\/\/datarade.ai. Accessed 04 Jan 2022"},{"key":"1679_CR25","unstructured":"Dawex (2021) Dawex. https:\/\/www.dawex.com\/en\/. Accessed 09 May 2021"},{"key":"1679_CR26","unstructured":"de\u00a0Alfaro L, Faella M, Polychronopoulos V, Shavlovsky M (2016) Incentives for truthful evaluations. CoRR arXiv:1608.07886"},{"issue":"2","key":"1679_CR27","doi-asserted-by":"publisher","first-page":"120","DOI":"10.1016\/j.rausp.2016.12.004","volume":"52","author":"D De Toni","year":"2017","unstructured":"De Toni D, Milan GS, Saciloto EB, Larentis F (2017) Pricing strategies and levels and their impact on corporate profitability. Revista de Administra\u00e7\u00e3o (S\u00e3o Paulo) 52(2):120\u2013133","journal-title":"Revista de Administra\u00e7\u00e3o (S\u00e3o Paulo)"},{"key":"1679_CR28","doi-asserted-by":"publisher","unstructured":"Deep S, Koutris P (2017a) The design of arbitrage-free data pricing schemes. In: Benedikt M, Orsi G (eds) 20th International conference on database theory, ICDT 2017, March 21\u201324, 2017, Venice, Italy, Schloss Dagstuhl - Leibniz-Zentrum f\u00fcr Informatik, LIPIcs, vol\u00a068, pp 12:1\u201312:18. https:\/\/doi.org\/10.4230\/LIPIcs.ICDT.2017.12","DOI":"10.4230\/LIPIcs.ICDT.2017.12"},{"key":"1679_CR29","doi-asserted-by":"publisher","unstructured":"Deep S, Koutris P (2017b) QIRANA: a framework for scalable query pricing. In: Salihoglu S, Zhou W, Chirkova R, Yang J, Suciu D (eds) Proceedings of the 2017 ACM international conference on management of data, SIGMOD conference 2017, Chicago, IL, USA, May 14\u201319, 2017. ACM, pp 699\u2013713. https:\/\/doi.org\/10.1145\/3035918.3064017","DOI":"10.1145\/3035918.3064017"},{"key":"1679_CR30","doi-asserted-by":"publisher","unstructured":"Devlin J, Chang M, Lee K, Toutanova K (2019) BERT: pre-training of deep bidirectional transformers for language understanding. In: Burstein J, Doran C, Solorio T (eds) Proceedings of the 2019 conference of the North American chapter of the Association for Computational Linguistics: human language technologies, NAACL-HLT 2019, Minneapolis, MN, USA, June 2\u20137, 2019, vol 1 (long and short papers). Association for Computational Linguistics, pp 4171\u20134186. https:\/\/doi.org\/10.18653\/v1\/n19-1423","DOI":"10.18653\/v1\/n19-1423"},{"key":"1679_CR31","volume-title":"Marketing: concepts and strategies","author":"S Dibb","year":"2005","unstructured":"Dibb S, Simkin L, Pride WM, Ferrell O (2005) Marketing: concepts and strategies, 5th edn. Houghton Mifflin, Abingdon","edition":"5"},{"key":"1679_CR32","doi-asserted-by":"publisher","unstructured":"Dwork C (2008) Differential privacy: a survey of results. In: Agrawal M, Du D, Duan Z, Li A (eds) Theory and applications of models of computation, 5th international conference, TAMC 2008, Xi\u2019an, China, April 25\u201329, 2008. Proceedings, lecture notes in computer science, vol 4978. Springer, pp 1\u201319. https:\/\/doi.org\/10.1007\/978-3-540-79228-4_1","DOI":"10.1007\/978-3-540-79228-4_1"},{"issue":"3","key":"1679_CR33","doi-asserted-by":"publisher","first-page":"774","DOI":"10.1016\/j.ejor.2013.09.031","volume":"234","author":"L Ensthaler","year":"2014","unstructured":"Ensthaler L, Giebe T (2014) Bayesian optimal knapsack procurement. Eur J Oper Res 234(3):774\u2013779. https:\/\/doi.org\/10.1016\/j.ejor.2013.09.031","journal-title":"Eur J Oper Res"},{"issue":"12","key":"1679_CR34","doi-asserted-by":"publisher","first-page":"1933","DOI":"10.14778\/3407790.3407800","volume":"13","author":"RC Fernandez","year":"2020","unstructured":"Fernandez RC, Subramaniam P, Franklin MJ (2020) Data market platforms: trading data assets to solve data problems. Proc VLDB Endow 13(12):1933\u20131947. https:\/\/doi.org\/10.14778\/3407790.3407800","journal-title":"Proc VLDB Endow"},{"key":"1679_CR35","doi-asserted-by":"publisher","first-page":"49","DOI":"10.1007\/978-3-319-69191-6_4","volume-title":"Software business","author":"SA Fricker","year":"2017","unstructured":"Fricker SA, Maksimov YV (2017) Pricing of data products in data marketplaces. In: Ojala A, Holmstr\u00f6m Olsson H, Werder K (eds) Software business. Springer, Cham, pp 49\u201366"},{"key":"1679_CR36","doi-asserted-by":"crossref","unstructured":"Fung C, Beschastnikh I (2019) Brokered agreements in multi-party machine learning. In: Proceedings of the 10th ACM SIGOPS Asia-Pacific workshop on systems, pp 69\u201375","DOI":"10.1145\/3343737.3343744"},{"key":"1679_CR37","unstructured":"Ghorbani A, Zou JY (2019) Data shapley: equitable valuation of data for machine learning. In: Chaudhuri K, Salakhutdinov R (eds) Proceedings of the 36th international conference on machine learning, ICML 2019, 9\u201315 June 2019, Long Beach, California, USA, PMLR, proceedings of machine learning research, vol\u00a097, pp 2242\u20132251. http:\/\/proceedings.mlr.press\/v97\/ghorbani19c.html"},{"key":"1679_CR38","doi-asserted-by":"publisher","unstructured":"Ghosh A, Roth A (2011) Selling privacy at auction. In: Shoham Y, Chen Y, Roughgarden T (eds) Proceedings 12th ACM conference on electronic commerce (EC-2011), San Jose, CA, USA, June 5\u20139, 2011. ACM, pp 199\u2013208. https:\/\/doi.org\/10.1145\/1993574.1993605","DOI":"10.1145\/1993574.1993605"},{"key":"1679_CR39","first-page":"47","volume":"4","author":"DB Gillies","year":"1959","unstructured":"Gillies DB (1959) Solutions to general non-zero-sum games. Contrib Theory Games 4:47\u201385","journal-title":"Contrib Theory Games"},{"key":"1679_CR40","doi-asserted-by":"publisher","unstructured":"Goel N, Faltings B (2019) Deep Bayesian trust: a dominant and fair incentive mechanism for crowd. In: The thirty-third AAAI conference on artificial intelligence, AAAI 2019, the thirty-first innovative applications of artificial intelligence conference, IAAI 2019, the ninth AAAI symposium on educational advances in artificial intelligence, EAAI 2019, Honolulu, Hawaii, USA, January 27\u2013February 1, 2019. AAAI Press, pp 1996\u20132003. https:\/\/doi.org\/10.1609\/aaai.v33i01.33011996","DOI":"10.1609\/aaai.v33i01.33011996"},{"key":"1679_CR41","unstructured":"Gur Y, Zeevi AJ, Besbes O (2014) Stochastic multi-armed-bandit problem with non-stationary rewards. In: Ghahramani Z, Welling M, Cortes C, Lawrence ND, Weinberger KQ (eds) Advances in neural information processing systems 27: annual conference on neural information processing systems 2014, December 8\u201313 2014, Montreal, Quebec, Canada, pp 199\u2013207. https:\/\/proceedings.neurips.cc\/paper\/2014\/hash\/903ce9225fca3e988c2af215d4e544d3-Abstract.html"},{"key":"1679_CR42","unstructured":"Han D, Tople S, Rogers A, Wooldridge MJ, Ohrimenko O, Tschiatschek S (2020) Replication-robust payoff-allocation with applications in machine learning marketplaces. CoRR arXiv:2006.14583"},{"key":"1679_CR43","unstructured":"Heckman JR, Boehmer EL, Peters EH, Davaloo M, Kurup NG (2015) A pricing model for data markets. iConference 2015 proceedings"},{"key":"1679_CR44","doi-asserted-by":"crossref","unstructured":"Hoeffding W (1994) Probability inequalities for sums of bounded random variables. In: The collected works of Wassily Hoeffding. Springer, pp 409\u2013426","DOI":"10.1007\/978-1-4612-0865-5_26"},{"key":"1679_CR45","doi-asserted-by":"publisher","unstructured":"Hu R, Gong Y (2020) Trading data for learning: incentive mechanism for on-device federated learning. In: IEEE global communications conference, GLOBECOM 2020, virtual event, Taiwan, December 7-11, 2020. IEEE, pp 1\u20136. https:\/\/doi.org\/10.1109\/GLOBECOM42002.2020.9322475","DOI":"10.1109\/GLOBECOM42002.2020.9322475"},{"key":"1679_CR46","unstructured":"Hu Z, Liang Y, Zhang J, Li Z, Liu Y (2018) Inference aided reinforcement learning for incentive mechanism design in crowdsourcing. In: Bengio S, Wallach HM, Larochelle H, Grauman K, Cesa-Bianchi N, Garnett R (eds) Advances in neural information processing systems 31: annual conference on neural information processing systems 2018, NeurIPS 2018, December 3\u20138, 2018, Montr\u00e9al, Canada, pp 5512\u20135522. https:\/\/proceedings.neurips.cc\/paper\/2018\/hash\/f2e43fa3400d826df4195a9ac70dca62-Abstract.html"},{"issue":"12","key":"1679_CR47","doi-asserted-by":"publisher","first-page":"2086","DOI":"10.14778\/3229863.3236266","volume":"11","author":"N Hynes","year":"2018","unstructured":"Hynes N, Dao D, Yan D, Cheng R, Song D (2018) A demonstration of sterling: a privacy-preserving data marketplace. Proc VLDB Endow 11(12):2086\u20132089. https:\/\/doi.org\/10.14778\/3229863.3236266","journal-title":"Proc VLDB Endow"},{"key":"1679_CR48","doi-asserted-by":"publisher","DOI":"10.1007\/978-1-349-15912-3","volume-title":"Modern cost-benefit methods","author":"G Irvin","year":"1978","unstructured":"Irvin G (1978) Modern cost-benefit methods. Macmillan Publishers Limited, London. https:\/\/doi.org\/10.1007\/978-1-349-15912-3"},{"issue":"11","key":"1679_CR49","doi-asserted-by":"publisher","first-page":"1610","DOI":"10.14778\/3342263.3342637","volume":"12","author":"R Jia","year":"2019","unstructured":"Jia R, Dao D, Wang B, Hubis FA, G\u00fcrel NM, Li B, Zhang C, Spanos CJ, Song D (2019) Efficient task-specific data valuation for nearest neighbor algorithms. Proc VLDB Endow 12(11):1610\u20131623. https:\/\/doi.org\/10.14778\/3342263.3342637","journal-title":"Proc VLDB Endow"},{"key":"1679_CR50","unstructured":"Jia R, Dao D, Wang B, Hubis FA, Hynes N, G\u00fcrel NM, Li B, Zhang C, Song D, Spanos CJ (2019) Towards efficient data valuation based on the Shapley value. In: Chaudhuri K, Sugiyama M (eds) The 22nd international conference on artificial intelligence and statistics, AISTATS 2019, 16\u201318 April 2019, Naha, Okinawa, Japan, PMLR, proceedings of machine learning research, vol\u00a089, pp 1167\u20131176. http:\/\/proceedings.mlr.press\/v89\/jia19a.html"},{"key":"1679_CR51","doi-asserted-by":"crossref","unstructured":"Jiang C, Gao L, Duan L, Huang J (2015) Economics of peer-to-peer mobile crowdsensing. In: 2015 IEEE global communications conference (GLOBECOM). IEEE, pp 1\u20136","DOI":"10.1109\/GLOCOM.2015.7417152"},{"key":"1679_CR52","doi-asserted-by":"publisher","unstructured":"Jin H, Su L, Chen D, Nahrstedt K, Xu J (2015) Quality of information aware incentive mechanisms for mobile crowd sensing systems. In: Shen SX, Sun Y, Chen J, Zhang J, Zussman G (eds) Proceedings of the 16th ACM international symposium on mobile ad hoc networking and computing, MobiHoc 2015, Hangzhou, China, June 22\u201325, 2015. ACM, pp 167\u2013176. https:\/\/doi.org\/10.1145\/2746285.2746310","DOI":"10.1145\/2746285.2746310"},{"key":"1679_CR53","doi-asserted-by":"publisher","unstructured":"Jin W, Xiao M, Li M, Guo L (2019) If you do not care about it, sell it: trading location privacy in mobile crowd sensing. In: 2019 IEEE conference on computer communications, INFOCOM 2019, Paris, France, April 29\u2013May 2, 2019. IEEE, pp 1045\u20131053. https:\/\/doi.org\/10.1109\/INFOCOM.2019.8737457","DOI":"10.1109\/INFOCOM.2019.8737457"},{"key":"1679_CR54","doi-asserted-by":"publisher","unstructured":"Jorgensen Z, Yu T, Cormode G (2015) Conservative or liberal? personalized differential privacy. In: Gehrke J, Lehner W, Shim K, Cha SK, Lohman GM (eds) 31st IEEE international conference on data engineering, ICDE 2015, Seoul, South Korea, April 13\u201317, 2015. IEEE Computer Society, pp 1023\u20131034. https:\/\/doi.org\/10.1109\/ICDE.2015.7113353","DOI":"10.1109\/ICDE.2015.7113353"},{"key":"1679_CR55","unstructured":"Kaggle (2022) Kaggle. https:\/\/www.kaggle.com\/datasets. Accessed 04 Jan 2022"},{"issue":"6","key":"1679_CR56","doi-asserted-by":"publisher","first-page":"10700","DOI":"10.1109\/JIOT.2019.2940820","volume":"6","author":"J Kang","year":"2019","unstructured":"Kang J, Xiong Z, Niyato D, Xie S, Zhang J (2019) Incentive mechanism for reliable federated learning: a joint optimization approach to combining reputation and contract theory. IEEE Internet Things J 6(6):10700\u201310714. https:\/\/doi.org\/10.1109\/JIOT.2019.2940820","journal-title":"IEEE Internet Things J"},{"key":"1679_CR57","unstructured":"Koh PW, Liang P (2017) Understanding black-box predictions via influence functions. In: Precup D, Teh YW (eds) Proceedings of the 34th international conference on machine learning, ICML 2017, Sydney, NSW, Australia, 6\u201311 August 2017, PMLR, proceedings of machine learning research, vol\u00a070, pp 1885\u20131894. http:\/\/proceedings.mlr.press\/v70\/koh17a.html"},{"key":"1679_CR58","doi-asserted-by":"publisher","unstructured":"Koutris P, Upadhyaya P, Balazinska M, Howe B, Suciu D (2012) Query-based data pricing. In: Benedikt M, Kr\u00f6tzsch M, Lenzerini M (eds) Proceedings of the 31st ACM SIGMOD-SIGACT-SIGART symposium on principles of database systems, PODS 2012, Scottsdale, AZ, USA, May 20\u201324, 2012. ACM, pp 167\u2013178. https:\/\/doi.org\/10.1145\/2213556.2213582","DOI":"10.1145\/2213556.2213582"},{"key":"1679_CR59","doi-asserted-by":"publisher","unstructured":"Koutris P, Upadhyaya P, Balazinska M, Howe B, Suciu D (2013) Toward practical query pricing with querymarket. In: Ross KA, Srivastava D, Papadias D (eds) Proceedings of the ACM SIGMOD international conference on management of data, SIGMOD 2013, New York, NY, USA, June 22\u201327, 2013. ACM, pp 613\u2013624. https:\/\/doi.org\/10.1145\/2463676.2465335","DOI":"10.1145\/2463676.2465335"},{"key":"1679_CR60","doi-asserted-by":"publisher","unstructured":"Koutsopoulos I (2013) Optimal incentive-driven design of participatory sensing systems. In: Proceedings of the IEEE INFOCOM 2013, Turin, Italy, April 14\u201319, 2013. IEEE, pp 1402\u20131410. https:\/\/doi.org\/10.1109\/INFCOM.2013.6566934","DOI":"10.1109\/INFCOM.2013.6566934"},{"key":"1679_CR61","doi-asserted-by":"publisher","DOI":"10.2200\/S00108ED1V01Y200802AIM003","volume-title":"Essentials of game theory: a concise multidisciplinary introduction. Synthesis lectures on artificial intelligence and machine learning","author":"K Leyton-Brown","year":"2008","unstructured":"Leyton-Brown K, Shoham Y (2008) Essentials of game theory: a concise multidisciplinary introduction. Synthesis lectures on artificial intelligence and machine learning. Morgan & Claypool Publishers, San Rafael. https:\/\/doi.org\/10.2200\/S00108ED1V01Y200802AIM003"},{"key":"1679_CR62","doi-asserted-by":"publisher","unstructured":"Li C, Li DY, Miklau G, Suciu D (2013) A theory of pricing private data. In: Tan W, Guerrini G, Catania B, Gounaris A (eds) Joint 2013 EDBT\/ICDT conferences, ICDT \u201913 proceedings, Genoa, Italy, March 18\u201322, 2013. ACM, pp 33\u201344. https:\/\/doi.org\/10.1145\/2448496.2448502","DOI":"10.1145\/2448496.2448502"},{"key":"1679_CR63","doi-asserted-by":"publisher","first-page":"15132","DOI":"10.1109\/ACCESS.2018.2806881","volume":"6","author":"F Liang","year":"2018","unstructured":"Liang F, Yu W, An D, Yang Q, Fu X, Zhao W (2018) A survey on big data market: pricing, trading and protection. IEEE Access 6:15132\u201315154","journal-title":"IEEE Access"},{"key":"1679_CR64","unstructured":"Lightsight (2022) Datastream identity dataset. https:\/\/datarade.ai\/data-products\/us-super-mobile2. Accessed 04 Jan 2022"},{"issue":"9","key":"1679_CR65","doi-asserted-by":"publisher","first-page":"757","DOI":"10.14778\/2732939.2732948","volume":"7","author":"B Lin","year":"2014","unstructured":"Lin B, Kifer D (2014) On arbitrage-free pricing for general data queries. Proc VLDB Endow 7(9):757\u2013768. https:\/\/doi.org\/10.14778\/2732939.2732948","journal-title":"Proc VLDB Endow"},{"key":"1679_CR66","doi-asserted-by":"crossref","unstructured":"Liu C, Chakraborty S, Mittal P (2016) Dependence makes you vulnberable: differential privacy under dependent tuples. In: 23rd annual network and distributed system security symposium, NDSS 2016, San Diego, California, USA, February 21\u201324, 2016. The Internet Society. http:\/\/wp.internetsociety.org\/ndss\/wp-content\/uploads\/sites\/25\/2017\/09\/dependence-makes-you-vulnerable-differential-privacy-under-dependent-tuples.pdf","DOI":"10.14722\/ndss.2016.23279"},{"issue":"6","key":"1679_CR67","doi-asserted-by":"publisher","first-page":"957","DOI":"10.14778\/3447689.3447700","volume":"14","author":"J Liu","year":"2021","unstructured":"Liu J, Lou J, Liu J, Xiong L, Pei J, Sun J (2021) Dealer: an end-to-end model marketplace with differential privacy. Proc VLDB Endow 14(6):957\u2013969. https:\/\/doi.org\/10.14778\/3447689.3447700","journal-title":"Proc VLDB Endow"},{"key":"1679_CR68","doi-asserted-by":"publisher","unstructured":"Liu Y, Chen Y (2017a) Machine-learning aided peer prediction. In: Daskalakis C, Babaioff M, Moulin H (eds) Proceedings of the 2017 ACM conference on economics and computation, EC \u201917, Cambridge, MA, USA, June 26\u201330, 2017. ACM, pp 63\u201380. https:\/\/doi.org\/10.1145\/3033274.3085126","DOI":"10.1145\/3033274.3085126"},{"key":"1679_CR69","doi-asserted-by":"crossref","unstructured":"Liu Y, Chen Y (2017) Sequential peer prediction: learning to elicit effort using posted prices. In: Singh SP, Markovitch S (eds) Proceedings of the thirty-first AAAI conference on artificial intelligence, February 4\u20139, 2017, San Francisco, California, USA. AAAI Press, pp 607\u2013613. http:\/\/aaai.org\/ocs\/index.php\/AAAI\/AAAI17\/paper\/view\/14970","DOI":"10.1609\/aaai.v31i1.10619"},{"key":"1679_CR70","unstructured":"Louis C (2020) Roundup of machine learning forecasts and market estimates, 2020. Forbes. https:\/\/www.forbes.com\/sites\/louiscolumbus\/2020\/01\/19\/roundup-of-machine-learning-forecasts-and-market-estimates-2020. Accessed 28 Jun 2021"},{"issue":"4","key":"1679_CR71","doi-asserted-by":"publisher","first-page":"2546","DOI":"10.1109\/COMST.2016.2582841","volume":"18","author":"NC Luong","year":"2016","unstructured":"Luong NC, Hoang DT, Wang P, Niyato D, Kim DI, Han Z (2016) Data collection and wireless communication in internet of things (IoT) using economic analysis and pricing models: a survey. IEEE Commun Surv Tutor 18(4):2546\u20132590","journal-title":"IEEE Commun Surv Tutor"},{"key":"1679_CR72","doi-asserted-by":"crossref","unstructured":"Ma L, Zhang C, Wang Y, Ruan W, Wang J, Tang W, Ma X, Gao X, Gao J (2020) Concare: personalized clinical feature embedding via capturing the healthcare context. In: The thirty-fourth AAAI conference on artificial intelligence, AAAI 2020, the thirty-second innovative applications of artificial intelligence conference, IAAI 2020, the tenth AAAI symposium on educational advances in artificial intelligence, EAAI 2020, New York, NY, USA, February 7\u201312, 2020. AAAI Press, pp 833\u2013840. https:\/\/aaai.org\/ojs\/index.php\/AAAI\/article\/view\/5428","DOI":"10.1609\/aaai.v34i01.5428"},{"key":"1679_CR73","unstructured":"Maleki S, Tran-Thanh L, Hines G, Rahwan T, Rogers A (2013) Bounding the estimation error of sampling-based Shapley value approximation with\/without stratifying. CoRR arXiv:1306.4265"},{"key":"1679_CR74","unstructured":"McMahan B, Moore E, Ramage D, Hampson S, y\u00a0Arcas BA (2017) Communication-efficient learning of deep networks from decentralized data. In: Singh A, Zhu XJ (eds) Proceedings of the 20th international conference on artificial intelligence and statistics, AISTATS 2017, 20\u201322 April 2017, Fort Lauderdale, FL, USA, PMLR, proceedings of machine learning research, vol\u00a054, pp 1273\u20131282. http:\/\/proceedings.mlr.press\/v54\/mcmahan17a.html"},{"key":"1679_CR75","doi-asserted-by":"crossref","unstructured":"Miao X, Gao Y, Chen L, Peng H, Yin J, Li Q (2020) Towards query pricing on incomplete data. IEEE Trans Knowl Data Eng","DOI":"10.1109\/TKDE.2020.3026031"},{"key":"1679_CR76","doi-asserted-by":"crossref","unstructured":"Muschalle A, Stahl F, L\u00f6ser A, Vossen G (2012) Pricing approaches for data markets. In: International workshop on business intelligence for the real-time enterprise. Springer, pp 129\u2013144","DOI":"10.1007\/978-3-642-39872-8_10"},{"issue":"1","key":"1679_CR77","doi-asserted-by":"publisher","first-page":"58","DOI":"10.1287\/moor.6.1.58","volume":"6","author":"RB Myerson","year":"1981","unstructured":"Myerson RB (1981) Optimal auction design. Math Oper Res 6(1):58\u201373","journal-title":"Math Oper Res"},{"key":"1679_CR78","volume-title":"The strategy and tactics of pricing: a guide to growing more profitably","author":"TT Nagle","year":"2010","unstructured":"Nagle TT, Hogan J (2010) The strategy and tactics of pricing: a guide to growing more profitably. Prentice Hall, Hoboken"},{"key":"1679_CR79","doi-asserted-by":"publisher","unstructured":"Nash A, Segoufin L, Vianu V (2007) Determinacy and rewriting of conjunctive queries using views: a progress report. In: Schwentick T, Suciu D (eds) Database theory\u2014ICDT 2007, 11th international conference, Barcelona, Spain, January 10\u201312, 2007, Proceedings, lecture notes in computer science, vol 4353. Springer, pp 59\u201373. https:\/\/doi.org\/10.1007\/11965893_5","DOI":"10.1007\/11965893_5"},{"key":"1679_CR80","doi-asserted-by":"publisher","first-page":"48","DOI":"10.1073\/pnas.36.1.48","volume":"36","author":"JF Nash","year":"1950","unstructured":"Nash JF (1950) Equilibrium points in $$n$$-person games. Proc Natl Acad Sci 36:48\u201349","journal-title":"Proc Natl Acad Sci"},{"key":"1679_CR81","unstructured":"Natarajan N, Dhillon IS, Ravikumar P, Tewari A (2013) Learning with noisy labels. In: Burges CJC, Bottou L, Ghahramani Z, Weinberger KQ (eds) Advances in neural information processing systems 26: 27th annual conference on neural information processing systems 2013. Proceedings of a meeting held December 5\u20138, 2013, Lake Tahoe, Nevada, United States, pp 1196\u20131204. https:\/\/proceedings.neurips.cc\/paper\/2013\/hash\/3871bd64012152bfb53fdf04b401193f-Abstract.html"},{"key":"1679_CR82","volume-title":"The brand flip: why customers now run companies-and how to profit from it","author":"M Neumeier","year":"2015","unstructured":"Neumeier M (2015) The brand flip: why customers now run companies-and how to profit from it. New Riders, San Francisco"},{"key":"1679_CR83","unstructured":"Nget R, Cao Y, Yoshikawa M (2017) How to balance privacy and money through pricing mechanism in personal data market. In: Degenhardt J, Kallumadi S, de\u00a0Rijke M, Si L, Trotman A, Xu Y (eds) Proceedings of the SIGIR 2017 workshop On eCommerce co-located with the 40th international ACM SIGIR conference on research and development in information retrieval, eCOM@SIGIR 2017, Tokyo, Japan, August 11, 2017. CEUR-WS.org, CEUR workshop proceedings, vol 2311. http:\/\/ceur-ws.org\/Vol-2311\/paper_15.pdf"},{"key":"1679_CR84","doi-asserted-by":"publisher","unstructured":"Niu C, Zheng Z, Wu F, Tang S, Gao X, Chen G (2018) Unlocking the value of privacy: trading aggregate statistics over private correlated data. In: Guo Y, Farooq F (eds) Proceedings of the 24th ACM SIGKDD international conference on knowledge discovery & data mining, KDD 2018, London, UK, August 19\u201323, 2018. ACM, pp 2031\u20132040. https:\/\/doi.org\/10.1145\/3219819.3220013","DOI":"10.1145\/3219819.3220013"},{"key":"1679_CR85","unstructured":"Ohrimenko O, Tople S, Tschiatschek S (2019) Collaborative machine learning markets with data-replication-robust payments. CoRR arXiv:1911.09052"},{"key":"1679_CR86","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2020.3045927","author":"J Pei","year":"2020","unstructured":"Pei J (2020) A survey on data pricing: from economics to data science. IEEE Trans Knowl Data Eng. https:\/\/doi.org\/10.1109\/TKDE.2020.3045927","journal-title":"IEEE Trans Knowl Data Eng"},{"key":"1679_CR87","doi-asserted-by":"crossref","unstructured":"Radanovic G, Faltings B (2016) Learning to scale payments in crowdsourcing with properboost. In: Ghosh A, Lease M (eds) Proceedings of the fourth AAAI conference on human computation and crowdsourcing, HCOMP 2016, 30 October\u20133 November, 2016, Austin, Texas, USA. AAAI Press, pp 179\u2013188. http:\/\/aaai.org\/ocs\/index.php\/HCOMP\/HCOMP16\/paper\/view\/14033","DOI":"10.1609\/hcomp.v4i1.13279"},{"issue":"4","key":"1679_CR88","doi-asserted-by":"publisher","first-page":"48:1","DOI":"10.1145\/2856102","volume":"7","author":"G Radanovic","year":"2016","unstructured":"Radanovic G, Faltings B, Jurca R (2016) Incentives for effort in crowdsourcing using the peer truth serum. ACM Trans Intell Syst Technol 7(4):48:1-48:28. https:\/\/doi.org\/10.1145\/2856102","journal-title":"ACM Trans Intell Syst Technol"},{"key":"1679_CR89","first-page":"1","volume":"9","author":"H Rauhut","year":"2010","unstructured":"Rauhut H (2010) Compressive sensing and structured random matrices. Theor Found Numer Methods Sparse Recovery 9:1\u201392","journal-title":"Theor Found Numer Methods Sparse Recovery"},{"key":"1679_CR90","unstructured":"REKLAIM (2022) Reklaim. https:\/\/www.reklaimyours.com. Accessed 04 Jan 2022"},{"key":"1679_CR91","unstructured":"Repository UML (2022) UCI machine learning repository. https:\/\/archive.ics.uci.edu\/ml\/index.php. Accessed 04 Jan 2022"},{"key":"1679_CR92","unstructured":"Richardson A, Filos-Ratsikas A, Faltings B (2019) Rewarding high-quality data via influence functions. CoRR arXiv:1908.11598"},{"key":"1679_CR93","doi-asserted-by":"publisher","first-page":"176","DOI":"10.1007\/978-3-030-63076-8_13","volume-title":"Federated learning\u2014privacy and incentive, lecture notes in computer science","author":"A Richardson","year":"2020","unstructured":"Richardson A, Filos-Ratsikas A, Faltings B (2020) Budget-bounded incentives for federated learning. In: Yang Q, Fan L, Yu H (eds) Federated learning\u2014privacy and incentive, lecture notes in computer science, vol 12500. Springer, Berlin, pp 176\u2013188. https:\/\/doi.org\/10.1007\/978-3-030-63076-8_13"},{"key":"1679_CR94","doi-asserted-by":"publisher","first-page":"53","DOI":"10.1016\/0377-0427(87)90125-7","volume":"20","author":"PJ Rousseeuw","year":"1987","unstructured":"Rousseeuw PJ (1987) Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. J Comput Appl Math 20:53\u201365","journal-title":"J Comput Appl Math"},{"issue":"1","key":"1679_CR95","doi-asserted-by":"publisher","first-page":"15","DOI":"10.1145\/2481528.2481532","volume":"42","author":"F Schomm","year":"2013","unstructured":"Schomm F, Stahl F, Vossen G (2013) Marketplaces for data: an initial survey. ACM SIGMOD Rec 42(1):15\u201326","journal-title":"ACM SIGMOD Rec"},{"key":"1679_CR96","unstructured":"Shah NB, Zhou D (2015) Double or nothing: multiplicative incentive mechanisms for crowdsourcing. In: Cortes C, Lawrence ND, Lee DD, Sugiyama M, Garnett R (eds) Advances in neural information processing systems 28: annual conference on neural information processing systems 2015, December 7\u201312, 2015, Montreal, Quebec, Canada, pp 1\u20139. https:\/\/proceedings.neurips.cc\/paper\/2015\/hash\/c81e728d9d4c2f636f067f89cc14862c-Abstract.html"},{"key":"1679_CR97","unstructured":"Shah NB, Zhou D (2016) No oops, you won\u2019t do it again: mechanisms for self-correction in crowdsourcing. In: Balcan M, Weinberger KQ (eds) Proceedings of the 33nd international conference on machine learning, ICML 2016, New York City, NY, USA, June 19\u201324, 2016. JMLR.org, JMLR workshop and conference proceedings, vol\u00a048, pp 1\u201310. http:\/\/proceedings.mlr.press\/v48\/shaha16.html"},{"key":"1679_CR98","unstructured":"Shah NB, Zhou D, Peres Y (2015) Approval voting and incentives in crowdsourcing. In: Bach FR, Blei DM (eds) Proceedings of the 32nd international conference on machine learning, ICML 2015, Lille, France, 6\u201311 July 2015. JMLR.org, JMLR workshop and conference proceedings, vol\u00a037, pp 10\u201319. http:\/\/proceedings.mlr.press\/v37\/shaha15.html"},{"key":"1679_CR99","first-page":"307","volume":"2","author":"LS Shapley","year":"1953","unstructured":"Shapley LS (1953) A value for n-person games. Contrib Theory Games 2:307\u2013317","journal-title":"Contrib Theory Games"},{"key":"1679_CR100","doi-asserted-by":"publisher","unstructured":"Shnayder V, Agarwal A, Frongillo RM, Parkes DC (2016) Informed truthfulness in multi-task peer prediction. In: Conitzer V, Bergemann D, Chen Y (eds) Proceedings of the 2016 ACM conference on economics and computation, EC \u201916, Maastricht, The Netherlands, July 24\u201328, 2016. ACM, pp 179\u2013196. https:\/\/doi.org\/10.1145\/2940716.2940790","DOI":"10.1145\/2940716.2940790"},{"key":"1679_CR101","unstructured":"Shnayder V, Frongillo RM, Parkes DC (2016b) Measuring performance of peer prediction mechanisms using replicator dynamics. In: Kambhampati S (ed) Proceedings of the twenty-fifth international joint conference on artificial intelligence, IJCAI 2016, New York, NY, USA, 9\u201315 July 2016. IJCAI\/AAAI Press, pp 2611\u20132617. http:\/\/www.ijcai.org\/Abstract\/16\/371"},{"key":"1679_CR102","unstructured":"Sim RHL, Zhang Y, Chan MC, Low BKH (2020) Collaborative machine learning with incentive-aware model rewards. In: Proceedings of the 37th international conference on machine learning, ICML 2020, 13\u201318 July 2020, virtual event, PMLR, proceedings of machine learning research, vol 119, pp 8927\u20138936. http:\/\/proceedings.mlr.press\/v119\/sim20a.html"},{"key":"1679_CR103","doi-asserted-by":"publisher","unstructured":"Singer Y (2010) Budget feasible mechanisms. In: 51th annual IEEE symposium on foundations of computer science, FOCS 2010, October 23\u201326, 2010, Las Vegas, Nevada, USA. IEEE Computer Society, pp 765\u2013774. https:\/\/doi.org\/10.1109\/FOCS.2010.78","DOI":"10.1109\/FOCS.2010.78"},{"key":"1679_CR104","unstructured":"Snowflake (2021) Snowflake data marketplace. https:\/\/www.snowflake.com\/data-marketplace\/. Accessed 09 May 2021"},{"issue":"4","key":"1679_CR105","doi-asserted-by":"publisher","first-page":"208","DOI":"10.1007\/s10272-019-0826-z","volume":"54","author":"M Spiekermann","year":"2019","unstructured":"Spiekermann M (2019) Data marketplaces: trends and monetisation of data goods. Intereconomics 54(4):208\u2013216","journal-title":"Intereconomics"},{"key":"1679_CR106","doi-asserted-by":"publisher","unstructured":"Stahl F, Vossen G (2016) Data quality scores for pricing on data marketplaces. In: Nguyen NT, Trawinski B, Fujita H, Hong T (eds) Intelligent information and database systems\u20148th Asian conference, ACIIDS 2016, Da Nang, Vietnam, March 14\u201316, 2016, proceedings, part I, lecture notes in computer science, vol 9621. Springer, pp 215\u2013224. https:\/\/doi.org\/10.1007\/978-3-662-49381-6_21","DOI":"10.1007\/978-3-662-49381-6_21"},{"key":"1679_CR107","doi-asserted-by":"publisher","unstructured":"Tang R, Wu H, Bao Z, Bressan S, Valduriez P (2013) The price is right\u2014models and algorithms for pricing data. In: Decker H, Lhotsk\u00e1 L, Link S, Basl J, Tjoa AM (eds) Database and expert systems applications\u201424th international conference, DEXA 2013, Prague, Czech Republic, August 26\u201329, 2013. Proceedings, part II, lecture notes in computer science, vol 8056. Springer, pp 380\u2013394. https:\/\/doi.org\/10.1007\/978-3-642-40173-2_31","DOI":"10.1007\/978-3-642-40173-2_31"},{"key":"1679_CR108","doi-asserted-by":"publisher","unstructured":"Tang R, Amarilli A, Senellart P, Bressan S (2014) Get a sample for a discount\u2014sampling-based XML data pricing. In: Decker H, Lhotsk\u00e1 L, Link S, Spies M, Wagner RR (eds) Database and expert systems applications\u201425th international conference, DEXA 2014, Munich, Germany, September 1\u20134, 2014. Proceedings, part I, lecture notes in computer science, vol 8644. Springer, pp 20\u201334. https:\/\/doi.org\/10.1007\/978-3-319-10073-9_3","DOI":"10.1007\/978-3-319-10073-9_3"},{"key":"1679_CR109","unstructured":"Tram\u00e8r F, Zhang F, Juels A, Reiter MK, Ristenpart T (2016) Stealing machine learning models via prediction APIs. In: Holz T, Savage S (eds) 25th USENIX security symposium, USENIX Security 16, Austin, TX, USA, August 10\u201312, 2016. USENIX Association, pp 601\u2013618. https:\/\/www.usenix.org\/conference\/usenixsecurity16\/technical-sessions\/presentation\/tramer"},{"key":"1679_CR110","unstructured":"Turk AM (2022) Amazon mechanical turk. https:\/\/www.mturk.com. Accessed 04 Jan 2022"},{"issue":"14","key":"1679_CR111","doi-asserted-by":"publisher","first-page":"1695","DOI":"10.14778\/3007328.3007335","volume":"9","author":"P Upadhyaya","year":"2016","unstructured":"Upadhyaya P, Balazinska M, Suciu D (2016) Price-optimal querying with data APIs. Proc VLDB Endow 9(14):1695\u20131706. https:\/\/doi.org\/10.14778\/3007328.3007335","journal-title":"Proc VLDB Endow"},{"key":"1679_CR112","first-page":"193:1","volume":"18","author":"JW Vaughan","year":"2017","unstructured":"Vaughan JW (2017) Making better use of the crowd: how crowdsourcing can advance machine learning research. J Mach Learn Res 18:193:1-193:46","journal-title":"J Mach Learn Res"},{"key":"1679_CR113","doi-asserted-by":"publisher","first-page":"153","DOI":"10.1007\/978-3-030-63076-8_11","volume-title":"Federated learning\u2014privacy and incentive, lecture notes in computer science","author":"T Wang","year":"2020","unstructured":"Wang T, Rausch J, Zhang C, Jia R, Song D (2020) A principled approach to data valuation for federated learning. In: Yang Q, Fan L, Yu H (eds) Federated learning\u2014privacy and incentive, lecture notes in computer science, vol 12500. Springer, Berlin, pp 153\u2013167. https:\/\/doi.org\/10.1007\/978-3-030-63076-8_11"},{"key":"1679_CR114","doi-asserted-by":"crossref","unstructured":"Yan T, Procaccia AD (2021) If you like Shapley then you\u2019ll love the core. In: Thirty-fifth AAAI conference on artificial intelligence, AAAI 2021, thirty-third conference on innovative applications of artificial intelligence, IAAI 2021, the eleventh symposium on educational advances in artificial intelligence, EAAI 2021, virtual event, February 2\u20139, 2021. AAAI Press, pp 5751\u20135759. https:\/\/ojs.aaai.org\/index.php\/AAAI\/article\/view\/16721","DOI":"10.1609\/aaai.v35i6.16721"},{"key":"1679_CR115","doi-asserted-by":"publisher","unstructured":"Yang D, Xue G, Fang X, Tang J (2012) Crowdsourcing to smartphones: incentive mechanism design for mobile phone sensing. In: Akan \u00d6B, Ekici E, Qiu L, Snoeren AC (eds) The 18th annual international conference on mobile computing and networking, Mobicom\u201912, Istanbul, Turkey, August 22\u201326, 2012. ACM, pp 173\u2013184. https:\/\/doi.org\/10.1145\/2348543.2348567","DOI":"10.1145\/2348543.2348567"},{"key":"1679_CR116","unstructured":"Yoon J, Arik S\u00d6, Pfister T (2020) Data valuation using reinforcement learning. In: Proceedings of the 37th international conference on machine learning, ICML 2020, 13\u201318 July 2020, virtual event, PMLR, proceedings of machine learning research, vol 119, pp 10842\u201310851. http:\/\/proceedings.mlr.press\/v119\/yoon20a.html"},{"key":"1679_CR117","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.cie.2017.08.008","volume":"112","author":"H Yu","year":"2017","unstructured":"Yu H, Zhang M (2017) Data pricing strategy based on data quality. Comput Ind Eng 112:1\u201310. https:\/\/doi.org\/10.1016\/j.cie.2017.08.008","journal-title":"Comput Ind Eng"},{"issue":"4","key":"1679_CR118","doi-asserted-by":"publisher","first-page":"58","DOI":"10.1109\/MIS.2020.2987774","volume":"35","author":"H Yu","year":"2020","unstructured":"Yu H, Liu Z, Liu Y, Chen T, Cong M, Weng X, Niyato D, Yang Q (2020) A sustainable incentive scheme for federated learning. IEEE Intell Syst 35(4):58\u201369. https:\/\/doi.org\/10.1109\/MIS.2020.2987774","journal-title":"IEEE Intell Syst"},{"key":"1679_CR119","doi-asserted-by":"crossref","unstructured":"Yu H, Yang K, Zhang T, Tsai Y, Ho T, Jin Y (2020b) Cloudleak: large-scale deep learning models stealing through adversarial examples. In: 27th annual network and distributed system security symposium, NDSS 2020, San Diego, California, USA, February 23\u201326, 2020. The Internet Society. https:\/\/www.ndss-symposium.org\/ndss-paper\/cloudleak-large-scale-deep-learning-models-stealing-through-adversarial-examples\/","DOI":"10.14722\/ndss.2020.24178"},{"key":"1679_CR120","doi-asserted-by":"crossref","unstructured":"Zhang M, Beltran F (2020) A survey of data pricing methods. SSRN","DOI":"10.2139\/ssrn.3609120"},{"key":"1679_CR121","unstructured":"Zhang M, Beltr\u00e1n F, Liu J (2020) Selling data at an auction under privacy constraints. In: Adams RP, Gogate V (eds) Proceedings of the thirty-sixth conference on uncertainty in artificial intelligence, UAI 2020, virtual online, August 3\u20136, 2020, proceedings of machine learning research, vol 124. AUAI Press, pp 669\u2013678. http:\/\/proceedings.mlr.press\/v124\/zhang20b.html"},{"issue":"1","key":"1679_CR122","doi-asserted-by":"publisher","first-page":"54","DOI":"10.1109\/COMST.2015.2415528","volume":"18","author":"X Zhang","year":"2016","unstructured":"Zhang X, Yang Z, Sun W, Liu Y, Tang S, Xing K, Mao X (2016) Incentives for mobile crowd sensing: a survey. IEEE Commun Surv Tutor 18(1):54\u201367. https:\/\/doi.org\/10.1109\/COMST.2015.2415528","journal-title":"IEEE Commun Surv Tutor"},{"key":"1679_CR123","doi-asserted-by":"crossref","unstructured":"Zhou X, Zheng H (2009) Trust: a general framework for truthful double spectrum auctions. In: IEEE INFOCOM 2009. IEEE, pp 999\u20131007","DOI":"10.1109\/INFCOM.2009.5062011"},{"key":"1679_CR124","unstructured":"Zhou Y, Porwal U, Zhang C, Ngo HQ, Nguyen L, R\u00e9 C, Govindaraju V (2014) Parallel feature selection inspired by group testing. In: Ghahramani Z, Welling M, Cortes C, Lawrence ND, Weinberger KQ (eds) Advances in neural information processing systems 27: annual conference on neural information processing systems 2014, December 8\u201313 2014, Montreal, Quebec, Canada, pp 3554\u20133562. https:\/\/proceedings.neurips.cc\/paper\/2014\/hash\/fb8feff253bb6c834deb61ec76baa893-Abstract.html"}],"container-title":["Knowledge and Information Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10115-022-01679-4.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s10115-022-01679-4\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10115-022-01679-4.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,2,5]],"date-time":"2023-02-05T03:16:48Z","timestamp":1675567008000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s10115-022-01679-4"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,5,13]]},"references-count":124,"journal-issue":{"issue":"6","published-print":{"date-parts":[[2022,6]]}},"alternative-id":["1679"],"URL":"https:\/\/doi.org\/10.1007\/s10115-022-01679-4","relation":{},"ISSN":["0219-1377","0219-3116"],"issn-type":[{"value":"0219-1377","type":"print"},{"value":"0219-3116","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,5,13]]},"assertion":[{"value":"14 July 2021","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"30 March 2022","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"1 April 2022","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"13 May 2022","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}