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Data"],"published-print":{"date-parts":[[2019,6,30]]},"abstract":"<jats:p>\n            The ever-increasing number of smartphone applications (apps) available on different app markets poses a challenge for personalized app recommendation. Conventional collaborative filtering-based recommendation methods suffer from sparse and binary user-app implicit feedback, which results in poor performance in discriminating user-app preferences. In this article, we first propose two\n            <jats:italic>kernel incorporated probabilistic matrix factorization<\/jats:italic>\n            models, which introduce app-categorical information to constrain the user and app latent features to be similar to their neighbors in the latent space. The two models are solved by\n            <jats:italic>Stochastic Gradient Descent<\/jats:italic>\n            with a user-oriented negative sampling scheme. To further improve the recommendation performance, we construct pseudo user-app ratings based on user-app usage information, and propose a novel\n            <jats:italic>kernelized non-negative matrix factorization<\/jats:italic>\n            by incorporating non-negative constraints on latent factors to predict user-app preferences. This model also leverages user--user and app--app similarities with regard to app-categorical information to mine the latent geometric structure in the pseudo-rating space. Adopting the\n            <jats:italic>Karush--Kuhn--Tucker<\/jats:italic>\n            conditions, a\n            <jats:italic>Multiplicative Updating Rules<\/jats:italic>\n            based optimization is proposed for model learning, and the convergence is proved by introducing an auxiliary function. The experimental results on a real user-app installation usage dataset show the comparable performance of our models with the state-of-the-art baselines in terms of two ranking-oriented evaluation metrics.\n          <\/jats:p>","DOI":"10.1145\/3320482","type":"journal-article","created":{"date-parts":[[2019,5,30]],"date-time":"2019-05-30T12:41:00Z","timestamp":1559220060000},"page":"1-27","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":13,"title":["Leveraging Kernel-Incorporated Matrix Factorization for App Recommendation"],"prefix":"10.1145","volume":"13","author":[{"given":"Chenyang","family":"Liu","sequence":"first","affiliation":[{"name":"Shanghai JiaoTong University, Shanghai, China"}]},{"given":"Jian","family":"Cao","sequence":"additional","affiliation":[{"name":"Shanghai JiaoTong University, Shanghai, China"}]},{"given":"Shanshan","family":"Feng","sequence":"additional","affiliation":[{"name":"Shandong Normal University, Jinan, China"}]}],"member":"320","published-online":{"date-parts":[[2019,5,29]]},"reference":[{"key":"e_1_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1145\/2339530.2339563"},{"key":"e_1_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.patrec.2011.01.012"},{"key":"e_1_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2010.231"},{"key":"e_1_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICDM.2008.57"},{"key":"e_1_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2013.7"},{"key":"e_1_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1145\/2684822.2685305"},{"key":"e_1_2_1_7_1","volume-title":"Proceedings of the 28th AAAI Conference on Artificial Intelligence. 30--36","author":"Fang Hui","year":"2014"},{"key":"e_1_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10489-018-1375-z"},{"key":"e_1_2_1_9_1","volume-title":"Proceedings of the International Conference on Machine Learning. 864--872","author":"G\u00f6nen Mehmet","year":"2013"},{"key":"e_1_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.5244\/C.23.9"},{"key":"e_1_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2011.2105496"},{"key":"e_1_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1145\/963770.963774"},{"key":"e_1_2_1_13_1","volume-title":"Sparse Nonnegative Matrix Factorization for Clustering","author":"Kim Jingu"},{"key":"e_1_2_1_15_1","volume-title":"Proceedings of the International Conference on Neural Information Processing Systems. 535--541","author":"Lee Daniel D."},{"key":"e_1_2_1_16_1","volume-title":"Proceedings of the 21st International Joint Conference on Artificial Intelligence. 1126","author":"Li Wu-Jun","year":"2009"},{"key":"e_1_2_1_17_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.sigpro.2010.01.019"},{"key":"e_1_2_1_18_1","doi-asserted-by":"publisher","DOI":"10.1145\/2484028.2484035"},{"key":"e_1_2_1_19_1","doi-asserted-by":"publisher","DOI":"10.1145\/2600428.2609560"},{"key":"e_1_2_1_20_1","doi-asserted-by":"publisher","DOI":"10.1145\/2983533"},{"key":"e_1_2_1_21_1","doi-asserted-by":"publisher","DOI":"10.1145\/1869652.1869653"},{"key":"e_1_2_1_22_1","doi-asserted-by":"publisher","DOI":"10.1137\/1.9781611974348.43"},{"key":"e_1_2_1_23_1","doi-asserted-by":"publisher","DOI":"10.1109\/TII.2014.2308433"},{"key":"e_1_2_1_24_1","volume-title":"Salakhutdinov","author":"Mnih Andriy","year":"2008"},{"key":"e_1_2_1_25_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICDM.2008.16"},{"key":"e_1_2_1_26_1","volume-title":"Proceedings of the International Joint Conference on Artificial Intelligence. 1593--1599","author":"Park Sunho","year":"2013"},{"key":"e_1_2_1_27_1","volume-title":"Proceedings of the 24th AAAI Conference on Artificial Intelligence. 563--568","author":"Porteous Ian","year":"2010"},{"key":"e_1_2_1_28_1","volume-title":"Proceedings of the 25th Conference on Uncertainty in Artificial Intelligence. 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