{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T04:28:27Z","timestamp":1750220907667,"version":"3.41.0"},"reference-count":42,"publisher":"Association for Computing Machinery (ACM)","issue":"6","license":[{"start":{"date-parts":[[2019,11,13]],"date-time":"2019-11-13T00:00:00Z","timestamp":1573603200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"DOI":"10.13039\/501100002322","name":"Coordena\u00e7\u00e3o de Aperfei\u00e7oamento de Pessoal de N\u00edvel Superior - Brasil","doi-asserted-by":"crossref","award":["001"],"award-info":[{"award-number":["001"]}],"id":[{"id":"10.13039\/501100002322","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100004901","name":"Funda\u00e7\u00e3o de Amparo \u00e0 Pesquisa do Estado de Minas Gerais","doi-asserted-by":"crossref","award":["2401572\/2018"],"award-info":[{"award-number":["2401572\/2018"]}],"id":[{"id":"10.13039\/501100004901","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100003593","name":"Conselho Nacional de Desenvolvimento Cient\u00edfico e Tecnol\u00f3gico","doi-asserted-by":"crossref","id":[{"id":"10.13039\/501100003593","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100009730","name":"Universidade Federal de Ouro Preto","doi-asserted-by":"crossref","id":[{"id":"10.13039\/501100009730","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["ACM Trans. Knowl. Discov. Data"],"published-print":{"date-parts":[[2019,12,31]]},"abstract":"<jats:p>E-news readers have increasingly at their disposal a broad set of news articles to read. Online newspaper sites use recommender systems to predict and to offer relevant articles to their users. Typically, these recommender systems do not leverage users\u2019 reading behavior. If we know how the topics-reads change in a reading session, we may lead to fine-tuned recommendations, for example, after reading a certain number of sports items, it may be counter-productive to keep recommending other sports news. The motivation for this article is the assumption that understanding user behavior when reading successive online news articles can help in developing better recommender systems. We propose five categories of stochastic models to describe this behavior depending on how the previous reading history affects the future choices of topics. We instantiated these five classes with many different stochastic processes covering short-term memory, revealed-preference, cumulative advantage, and geometric sojourn models. Our empirical study is based on large datasets of E-news from two online newspapers. We collected data from more than 13 million users who generated more than 23 million reading sessions, each one composed by the successive clicks of the users on the posted news. We reduce each user session to the sequence of reading news topics. The models were fitted and compared using the Akaike Information Criterion and the Brier Score. We found that the best models are those in which the user moves through topics influenced only by their most recent readings. Our models were also better to predict the next reading than the recommender systems currently used in these journals showing that our models can improve user satisfaction.<\/jats:p>","DOI":"10.1145\/3362695","type":"journal-article","created":{"date-parts":[[2019,11,13]],"date-time":"2019-11-13T22:02:32Z","timestamp":1573682552000},"page":"1-27","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":1,"title":["In Search of a Stochastic Model for the E-News Reader"],"prefix":"10.1145","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7320-7681","authenticated-orcid":false,"given":"Br\u00e1ulio M.","family":"Veloso","sequence":"first","affiliation":[{"name":"Departamento de Computa\u00e7\u00e3o, Universidade Federal de Ouro Preto, Ouro Preto, MG, Brazil"}]},{"given":"Renato M.","family":"Assun\u00e7\u00e3o","sequence":"additional","affiliation":[{"name":"Departamento de Ci\u00eancia da Computa\u00e7\u00e3o, Universidade Federal de Minas Gerais, MG, Brazil"}]},{"given":"Anderson A.","family":"Ferreira","sequence":"additional","affiliation":[{"name":"Departamento de Computa\u00e7\u00e3o, Universidade Federal de Ouro Preto, Ouro Preto, MG, Brazil"}]},{"given":"Nivio","family":"Ziviani","sequence":"additional","affiliation":[{"name":"Departamento de Ci\u00eancia da Computa\u00e7\u00e3o, Universidade Federal de Minas Gerais, MG, Brazil"}]}],"member":"320","published-online":{"date-parts":[[2019,11,13]]},"reference":[{"key":"e_1_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1145\/1148170.1148177"},{"key":"e_1_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1145\/2124295.2124337"},{"key":"e_1_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1109\/TAC.1974.1100705"},{"volume-title":"C","year":"2017","author":"Bai Xiao","key":"e_1_2_1_4_1"},{"key":"e_1_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1145\/2792838.2800186"},{"volume-title":"The Editor","year":"2007","author":"Belenky Alexander","key":"e_1_2_1_6_1"},{"volume-title":"Proceedings of the 17th International Conference on World Wide Web (WWW\u201908)","author":"Bilenko Mikhail","key":"e_1_2_1_7_1"},{"volume-title":"Proceedings of the 2007 ACM Conference on Recommender Systems (RecSys\u201907)","author":"Bogers Toine","key":"e_1_2_1_8_1"},{"key":"e_1_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.1175\/1520-0493(1950)078<0001:VOFEIT>2.0.CO;2"},{"volume-title":"Anderson","year":"2003","author":"Burnham Kenneth P.","key":"e_1_2_1_10_1"},{"volume-title":"Time-aware recommender systems: A comprehensive survey and analysis of existing evaluation protocols. User Modeling and User-Adapted Interaction 24, 1 (01","year":"2014","author":"Campos Pedro G.","key":"e_1_2_1_11_1"},{"key":"e_1_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1002\/cjs.10014"},{"key":"e_1_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.1080\/01621459.2017.1345742"},{"volume-title":"Proceedings of ACM SIGIR Workshop on Recommender Systems: Implementarion and Evaluation. ACM","year":"1999","author":"Claypool Mark","key":"e_1_2_1_14_1"},{"key":"e_1_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.1145\/1242572.1242610"},{"key":"e_1_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.1145\/2124295.2124315"},{"key":"e_1_2_1_17_1","doi-asserted-by":"publisher","DOI":"10.1145\/3079628.3079636"},{"key":"e_1_2_1_18_1","doi-asserted-by":"publisher","DOI":"10.1145\/3109859.3109894"},{"key":"e_1_2_1_19_1","doi-asserted-by":"publisher","DOI":"10.1145\/2637002.2637038"},{"key":"e_1_2_1_20_1","doi-asserted-by":"publisher","DOI":"10.1214\/17-AOAS1132"},{"volume-title":"Minin","year":"2018","author":"Guttorp Peter","key":"e_1_2_1_21_1"},{"volume-title":"Proceedings of the 28th International Conference on Machine Learning (ICML\u201911)","year":"2011","author":"Hern\u00e1ndez-Orallo Jos\u00e9","key":"e_1_2_1_22_1"},{"key":"e_1_2_1_23_1","first-page":"2813","article-title":"A unified view of performance metrics: Translating threshold choice into expected classification loss","author":"Hern\u00e1ndez-Orallo Jos\u00e9","year":"2012","journal-title":"Journal of Machine Learning Research 13"},{"key":"e_1_2_1_24_1","doi-asserted-by":"publisher","DOI":"10.1145\/2872427.2883006"},{"key":"e_1_2_1_25_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICDM.2008.22"},{"key":"e_1_2_1_26_1","volume-title":"Proceedings of the 12th International Society for Music Information Retrieval Conference","volume":"11","author":"Hu Yajie","year":"2011"},{"key":"e_1_2_1_27_1","doi-asserted-by":"publisher","DOI":"10.1137\/1.9781611974348.50"},{"key":"e_1_2_1_28_1","doi-asserted-by":"publisher","DOI":"10.1145\/2835776.2835833"},{"key":"e_1_2_1_29_1","unstructured":"Vadim Lavrusik. 2009. 12 Things Newspapers Should Do to Survive. Retrieved from http:\/\/mashable.com\/2009\/08\/14\/newspaper-survival\/#LKdF2UTVJuqy.  Vadim Lavrusik. 2009. 12 Things Newspapers Should Do to Survive. Retrieved from http:\/\/mashable.com\/2009\/08\/14\/newspaper-survival\/#LKdF2UTVJuqy."},{"volume-title":"Proceedings of the 19th International Conference on World Wide Web (WWW\u201910)","author":"Li Lihong","key":"e_1_2_1_30_1"},{"key":"e_1_2_1_31_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2013.11.020"},{"key":"e_1_2_1_32_1","doi-asserted-by":"publisher","DOI":"10.1145\/1451983.1451986"},{"key":"e_1_2_1_33_1","doi-asserted-by":"publisher","DOI":"10.1108\/00220410510632040"},{"volume-title":"Proceedings of the 10th ACM Conference on Recommender Systems. ACM, 333--340","author":"Lopes Ramon","key":"e_1_2_1_34_1"},{"key":"e_1_2_1_35_1","doi-asserted-by":"publisher","DOI":"10.1175\/1520-0450(1973)012<0595:ANVPOT>2.0.CO;2"},{"volume-title":"The Model Thinker","author":"Page Scott E.","key":"e_1_2_1_36_1"},{"key":"e_1_2_1_37_1","doi-asserted-by":"publisher","DOI":"10.1002\/9780470746684"},{"key":"e_1_2_1_38_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-20161-5_44"},{"volume-title":"An Introduction to Stochastic Modeling","author":"Pinsky Mark","key":"e_1_2_1_39_1"},{"volume-title":"Proceedings of the 9th International AAAI Conference on Web-Blogs and Social Media. Association for the Advancement of Artificial Intelligence","author":"Reis Julio","key":"e_1_2_1_40_1"},{"volume-title":"Workshop and challenge on news recommender systems. In Proceedings of the 7th ACM Conference on Recommender Systems (RecSys\u201913)","year":"2013","author":"Tavakolifard Mozhgan","key":"e_1_2_1_41_1"},{"key":"e_1_2_1_42_1","doi-asserted-by":"publisher","DOI":"10.1145\/2939672.2939792"}],"container-title":["ACM Transactions on Knowledge Discovery from Data"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3362695","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3362695","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T23:44:54Z","timestamp":1750203894000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3362695"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,11,13]]},"references-count":42,"journal-issue":{"issue":"6","published-print":{"date-parts":[[2019,12,31]]}},"alternative-id":["10.1145\/3362695"],"URL":"https:\/\/doi.org\/10.1145\/3362695","relation":{},"ISSN":["1556-4681","1556-472X"],"issn-type":[{"type":"print","value":"1556-4681"},{"type":"electronic","value":"1556-472X"}],"subject":[],"published":{"date-parts":[[2019,11,13]]},"assertion":[{"value":"2018-12-01","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2019-09-01","order":1,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2019-11-13","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}