{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,3]],"date-time":"2025-11-03T22:55:05Z","timestamp":1762210505653,"version":"3.41.0"},"reference-count":11,"publisher":"Association for Computing Machinery (ACM)","issue":"2","license":[{"start":{"date-parts":[[2007,12,1]],"date-time":"2007-12-01T00:00:00Z","timestamp":1196467200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"name":"ASTOR","award":["NKFP 2\/004\/05"],"award-info":[{"award-number":["NKFP 2\/004\/05"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["SIGKDD Explor. Newsl."],"published-print":{"date-parts":[[2007,12]]},"abstract":"<jats:p>KDD Cup 2007 focuses on predicting aspects of movie rating behavior. We present our prediction method for Task 1 \"Who Rated What in 2006\" where the goal is to predict which users rated which movies in 2006. We use the combination of the following methods, listed in the order of their accuracy:<\/jats:p><jats:p>\u2022 The predicted number of ratings for each movie based on time series analysis, also using movie and DVD release dates and movie series detection by the edit distance of the titles.<\/jats:p><jats:p>\u2022 The predicted number of ratings by each user by using the fact that ratings were sampled proportional to the margin.<\/jats:p><jats:p>\u2022 The low rank approximation of the 0-1 matrix of known user-movie pairs with rating.<\/jats:p><jats:p>\u2022 Prediction by using the movie-movie similarity matrix.<\/jats:p><jats:p>\u2022 Association rules obtained by frequent sequence mining of user ratings considered as ordered itemsets.<\/jats:p><jats:p>By combining the predictions by linear regression we obtained a prediction with root mean squared error 0.256. The first runner up result was 0.263 while a pure all zeroes prediction already gives 0.279, indicating the hardness of the task.<\/jats:p>","DOI":"10.1145\/1345448.1345460","type":"journal-article","created":{"date-parts":[[2008,2,28]],"date-time":"2008-02-28T14:02:33Z","timestamp":1204207353000},"page":"53-56","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":4,"title":["KDD Cup 2007 task 1 winner report"],"prefix":"10.1145","volume":"9","author":[{"given":"Mikl\u00f3s","family":"Kurucz","sequence":"first","affiliation":[{"name":"Data Mining and Web search Research Group, Informatics Laboratory; Computer and Automation Research Institute of the Hungarian Academy of Sciences"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Andr\u00e1s A.","family":"Bencz\u00far","sequence":"additional","affiliation":[{"name":"Data Mining and Web search Research Group, Informatics Laboratory; Computer and Automation Research Institute of the Hungarian Academy of Sciences"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tam\u00e1s","family":"Kiss","sequence":"additional","affiliation":[{"name":"Data Mining and Web search Research Group, Informatics Laboratory; Computer and Automation Research Institute of the Hungarian Academy of Sciences"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Istv\u00e1n","family":"Nagy","sequence":"additional","affiliation":[{"name":"Data Mining and Web search Research Group, Informatics Laboratory; Computer and Automation Research Institute of the Hungarian Academy of Sciences"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Adrienn","family":"Szab\u00f3","sequence":"additional","affiliation":[{"name":"Data Mining and Web search Research Group, Informatics Laboratory; Computer and Automation Research Institute of the Hungarian Academy of Sciences"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Bal\u00e1zs","family":"Torma","sequence":"additional","affiliation":[{"name":"Data Mining and Web search Research Group, Informatics Laboratory; Computer and Automation Research Institute of the Hungarian Academy of Sciences"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2007,12]]},"reference":[{"key":"e_1_2_1_1_1","first-page":"487","volume-title":"International Conference on Very Large Data Bases (VLDB)","author":"Agrawal R.","year":"1994"},{"volume-title":"KDD Cup and Workshop in conjunction with KDD 2007","year":"2007","author":"Bennett J.","key":"e_1_2_1_2_1"},{"volume-title":"University of Tennessee","year":"1992","author":"Berry M. W.","key":"e_1_2_1_3_1"},{"volume-title":"Baltimore","year":"1983","author":"Golub G. H.","key":"e_1_2_1_4_1"},{"key":"e_1_2_1_5_1","doi-asserted-by":"crossref","first-page":"193","DOI":"10.1111\/j.2517-6161.1953.tb00135.x","article-title":"New light on the correlation coefficient and its transforms","volume":"15","author":"Hotelling H.","year":"1953","journal-title":"Journal of the Royal Statistical Society B"},{"volume-title":"KDD Cup and Workshop in conjunction with KDD 2007","year":"2007","author":"Kurucz M.","key":"e_1_2_1_6_1"},{"key":"e_1_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1145\/1348549.1348559"},{"key":"e_1_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1145\/375360.375365"},{"key":"e_1_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.1145\/1345448.1345463"},{"key":"e_1_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.1145\/371920.372071"},{"key":"e_1_2_1_11_1","unstructured":"I. H. Witten and E. Frank. Data Mining: Practical Machine Learning Tools and Techniques. Morgan Kaufmann Series in Data Management Systems. Morgan Kaufmann second edition June 2005. I. H. Witten and E. Frank. Data Mining: Practical Machine Learning Tools and Techniques. Morgan Kaufmann Series in Data Management Systems. Morgan Kaufmann second edition June 2005."}],"container-title":["ACM SIGKDD Explorations Newsletter"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/1345448.1345460","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/1345448.1345460","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T20:22:21Z","timestamp":1750278141000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/1345448.1345460"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2007,12]]},"references-count":11,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2007,12]]}},"alternative-id":["10.1145\/1345448.1345460"],"URL":"https:\/\/doi.org\/10.1145\/1345448.1345460","relation":{},"ISSN":["1931-0145","1931-0153"],"issn-type":[{"type":"print","value":"1931-0145"},{"type":"electronic","value":"1931-0153"}],"subject":[],"published":{"date-parts":[[2007,12]]},"assertion":[{"value":"2007-12-01","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}