{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,20]],"date-time":"2026-06-20T01:00:24Z","timestamp":1781917224215,"version":"3.54.5"},"publisher-location":"New York, New York, USA","reference-count":31,"publisher":"ACM Press","license":[{"start":{"date-parts":[[2018,1,1]],"date-time":"2018-01-01T00:00:00Z","timestamp":1514764800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2018]]},"DOI":"10.1145\/3176349.3176885","type":"proceedings-article","created":{"date-parts":[[2018,3,1]],"date-time":"2018-03-01T20:06:04Z","timestamp":1519934764000},"page":"313-316","source":"Crossref","is-referenced-by-count":31,"title":["Understanding Music Listening Intents During Daily Activities with Implications for Contextual Music Recommendation"],"prefix":"10.1145","author":[{"given":"Sergey","family":"Volokhin","sequence":"first","affiliation":[{"name":"Emory University, Atlanta, GA, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Eugene","family":"Agichtein","sequence":"additional","affiliation":[{"name":"Emory University, Atlanta, GA, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","reference":[{"key":"key-10.1145\/3176349.3176885-1","unstructured":"2014. Google Activity Recognition Client. (2014). Retrieved October 22, 2017 from goo.gl\/V98vUs"},{"key":"key-10.1145\/3176349.3176885-2","unstructured":"Gediminas Adomavicius and Alexander Tuzhilin. 2011. Context-Aware Recommender Systems. Springer, 217--253. https:\/\/doi.org\/10.1007\/978-0--387--85820--3_7"},{"key":"key-10.1145\/3176349.3176885-3","doi-asserted-by":"crossref","unstructured":"Ivana Andjelkovic, Denis Parra, and John O'Donovan. 2016. Moodplay: Interactive Mood-based Music Discovery and Recommendation. In Proceedings of the 2016 Conference on User Modeling Adaptation and Personalization (UMAP '16). 275--279. https:\/\/doi.org\/10.1145\/2930238.2930280","DOI":"10.1145\/2930238.2930280"},{"key":"key-10.1145\/3176349.3176885-4","unstructured":"Linas Baltrunas and Xavier Amatriain. 2009. Towards Time-Dependant Recommendation based on Implicit Feedback. In Proc. of RECSYS."},{"key":"key-10.1145\/3176349.3176885-5","unstructured":"Fredrik Boström. 2017. AndroMedia - Towards a Context-aware Mobile Music Recommender. Master's thesis."},{"key":"key-10.1145\/3176349.3176885-6","doi-asserted-by":"crossref","unstructured":"Matthias Braunhofer, Marius Kaminskas, and Francesco Ricci. 2013. Locationaware music recommendation. International Journal of Multimedia Information Retrieval 2, 1 (01 Mar 2013), 31--44. https:\/\/doi.org\/10.1007\/s13735-012-0032--2","DOI":"10.1007\/s13735-012-0032-2"},{"key":"key-10.1145\/3176349.3176885-7","doi-asserted-by":"crossref","unstructured":"Steven Brown and Michael et. al Martinez. 2004. Passive music listening spontaneously engages limbic and paralimbic systems. Neuroreport 15, 13 (2004).","DOI":"10.1097\/00001756-200409150-00008"},{"key":"key-10.1145\/3176349.3176885-8","doi-asserted-by":"crossref","unstructured":"Zhiyong Cheng and Jialie Shen. 2016. On Effective Location-Aware Music Recommendation. ACM Trans. Inf. Syst. 34, 2, Article 13 (April 2016), 32 pages. https:\/\/doi.org\/10.1145\/2846092","DOI":"10.1145\/2846092"},{"key":"key-10.1145\/3176349.3176885-9","doi-asserted-by":"crossref","unstructured":"Hal Daumé, III and Eric Brill. 2004. Web Search Intent Induction via Automatic Query Reformulation. In Proc. of HLT-NAACL 2004: Short Papers (HLT-NAACLShort '04). ACM, 49--52. http:\/\/dl.acm.org\/citation.cfm'id=1613984.1613997","DOI":"10.3115\/1613984.1613997"},{"key":"key-10.1145\/3176349.3176885-10","unstructured":"Ricardo Dias, Manuel J. Fonseca, and Ricardo Cunha. 2014. A User-centered Music Recommendation Approach for Daily Activities. In CBRecSys@RecSys."},{"key":"key-10.1145\/3176349.3176885-11","unstructured":"Bernard J Jansen, Danielle L Booth, and Amanda Spink. 2007. Determining the user intent of web search engine queries. In Proceedings of the 16th internationalconference on World Wide Web. ACM, 1149--1150."},{"key":"key-10.1145\/3176349.3176885-12","unstructured":"Juuso Kaitila. 2017. A content-based music recommender system. (2017)."},{"key":"key-10.1145\/3176349.3176885-13","doi-asserted-by":"crossref","unstructured":"Wei-Po Lee, Chun-Ting Chen, Jhih-Yuan Huang, and Jhen-Yi Liang. 2017. A smartphone-based activity-aware system for music streaming recommendation. Knowledge-Based Systems 131 (2017). https:\/\/doi.org\/10.1016\/j.knosys.2017.06.002","DOI":"10.1016\/j.knosys.2017.06.002"},{"key":"key-10.1145\/3176349.3176885-14","doi-asserted-by":"crossref","unstructured":"Young-Seol Lee and Sung-Bae Cho. 2011. Activity Recognition Using Hierarchical Hidden Markov Models on a Smartphone with 3D Accelerometer. 460--467. https: \/\/doi.org\/10.1007\/978--3--642--21219--2_58","DOI":"10.1007\/978-3-642-21219-2_58"},{"key":"key-10.1145\/3176349.3176885-15","unstructured":"Daniel J. Levitin and James McGill. 2007. Life Soundtracks: The uses of music in everyday life. (2007)."},{"key":"key-10.1145\/3176349.3176885-16","unstructured":"Cathy Mckinney, Michael Antoni, Mahendra Kumar, Frederick C. Tims, and Philip Mccabe. 1997. Effects of Guided Imagery and Music (GIM) Therapy on Mood and Cortisol in Healthy Adults. 16 (08 1997), 390--400."},{"key":"key-10.1145\/3176349.3176885-17","doi-asserted-by":"crossref","unstructured":"Adrian C. North, David J. Hargreaves, and Jon J. Hargreaves. 2004. Uses of Music in Everyday Life. Music Perception: An Interdisciplinary Journal 22, 1 (2004), 41--77. https:\/\/doi.org\/10.1525\/mp.2004.22.1.41 arXiv:http:\/\/mp.ucpress.edu\/content\/22\/1\/41.full.pdf","DOI":"10.1525\/mp.2004.22.1.41"},{"key":"key-10.1145\/3176349.3176885-18","unstructured":"The International Federation of the Phonographic Industry. 2017. Connecting with music. Music consumer insight report. (2017). http:\/\/www.ifpi.org\/ downloads\/Music-Consumer-Insight-Report-2017.pdf"},{"key":"key-10.1145\/3176349.3176885-19","unstructured":"So-Hyun Park, Sun-Young Ihm, Wu-In Jang, Aziz Nasridinov, and Young-Ho Park. 2015. A Music Recommendation Method with Emotion Recognition Using Ranked Attributes. 1065--1070. https:\/\/doi.org\/10.1007\/978--3--662--45402--2_151"},{"key":"key-10.1145\/3176349.3176885-20","doi-asserted-by":"crossref","unstructured":"Daniel E. Rose and Danny Levinson. 2004. Understanding User Goals in Web Search. In Proc. of WWW. 13--19. https:\/\/doi.org\/10.1145\/988672.988675","DOI":"10.1145\/988672.988675"},{"key":"key-10.1145\/3176349.3176885-21","doi-asserted-by":"crossref","unstructured":"Diego Sánchez-Moreno, Ana B. Gil González, M. Dolores Muñoz Vicente, Vivian F. López Batista, and María N. Moreno García. 2016. A collaborative filtering method for music recommendation using playing coefficients for artists and users. Expert Systems with Applications 66, Supplement C (2016), 234 -- 244. https:\/\/doi.org\/10.1016\/j.eswa.2016.09.019","DOI":"10.1016\/j.eswa.2016.09.019"},{"key":"key-10.1145\/3176349.3176885-22","unstructured":"Yading Song, Simon Dixon, and Marcus Pearce. 2012. A Survey of Music Recommendation Systems and Future Perspectives. In 9th International Symposium on Computer Music Modelling and Retrieval (CMMR 2012). London."},{"key":"key-10.1145\/3176349.3176885-23","unstructured":"Internet World Stats. 2017. The Internet Big Picture. World Internet Users and 2017 Population Stats. (2017). http:\/\/www.internetworldstats.com\/stats.htm"},{"key":"key-10.1145\/3176349.3176885-24","unstructured":"Yonatan Vaizman, Katherine Ellis, and Gert R. G. Lanckriet. 2016. Recognizing Detailed Human Context In-the-Wild from Smartphones and Smartwatches. CoRR abs\/1609.06354 (2016). http:\/\/arxiv.org\/abs\/1609.06354"},{"key":"key-10.1145\/3176349.3176885-25","doi-asserted-by":"crossref","unstructured":"Saul Vargas, Pablo Castells, and David Vallet. 2011. Intent-oriented diversity in recommender systems. In Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval. ACM, 1211.","DOI":"10.1145\/2009916.2010124"},{"key":"key-10.1145\/3176349.3176885-26","doi-asserted-by":"crossref","unstructured":"Xinxi Wang, David Rosenblum, and Ye Wang. 2012. Context-aware Mobile Music Recommendation for Daily Activities. In Proc. of the ACM International Conference on Multimedia (MM '12). ACM, New York, NY, USA, 99--108. https: \/\/doi.org\/10.1145\/2393347.2393368","DOI":"10.1145\/2393347.2393368"},{"key":"key-10.1145\/3176349.3176885-27","doi-asserted-by":"crossref","unstructured":"Xinxi Wang and Ye Wang. 2014. Improving Content-based and Hybrid Music Recommendation Using Deep Learning. In Proc. of ACM International Conference on Multimedia (MM'14). 627--636. https:\/\/doi.org\/10.1145\/2647868.2654940","DOI":"10.1145\/2647868.2654940"},{"key":"key-10.1145\/3176349.3176885-28","unstructured":"Zhe Xing, Xinxi Wang, and Ye Wang. 2014. Enhancing Collaborative Filtering Music Recommendation by Balancing Exploration and Exploitation.. In Proc. of ISMIR. 445--450."},{"key":"key-10.1145\/3176349.3176885-29","unstructured":"Yan Yan, Tianlong Liu, and Zhenyu Wang. 2015. A Music Recommendation Algorithm Based on Hybrid Collaborative Filtering Technique. Springer Singapore, Singapore, 233--240. https:\/\/doi.org\/10.1007\/978--981--10-0080--5_23"},{"key":"key-10.1145\/3176349.3176885-30","unstructured":"Jinhyeok Yang, WooJoung Chae, SunYeob Kim, and Hyebong Choi. 2016. EmotionAware Music Recommendation. Springer International Publishing, Cham, 110--121. https:\/\/doi.org\/10.1007\/978--3--319--40355--7_11"},{"key":"key-10.1145\/3176349.3176885-31","doi-asserted-by":"crossref","unstructured":"Billy Yapriady and Alexandra L. Uitdenbogerd. 2005. Combining Demographic Data with Collaborative Filtering for Automatic Music Recommendation. 201--207. https:\/\/doi.org\/10.1007\/11554028_29","DOI":"10.1007\/11554028_29"}],"event":{"name":"the 2018 Conference","location":"New Brunswick, NJ, USA","acronym":"CHIIR '18","number":"2018","sponsor":["SIGIR, ACM Special Interest Group on Information Retrieval","SIGCHI, ACM Special Interest Group on Computer-Human Interaction"],"start":{"date-parts":[[2018,3,11]]},"end":{"date-parts":[[2018,3,15]]}},"container-title":["Proceedings of the 2018 Conference on Human Information Interaction&Retrieval - CHIIR '18"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3176349.3176885","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/dl.acm.org\/ft_gateway.cfm?id=3176885&ftid=1948299&dwn=1","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T02:11:32Z","timestamp":1750212692000},"score":1,"resource":{"primary":{"URL":"http:\/\/dl.acm.org\/citation.cfm?doid=3176349.3176885"}},"subtitle":[],"proceedings-subject":"Human Information Interaction&Retrieval","short-title":[],"issued":{"date-parts":[[2018]]},"references-count":31,"URL":"https:\/\/doi.org\/10.1145\/3176349.3176885","relation":{},"subject":[],"published":{"date-parts":[[2018]]}}}