Moreopt: A goal programming based movie recommender system
•Combining content information of movie features with collaborative filtering approach.•Using a goal programming model in the content-based method to predict missing ratings.•Overcome data sparsity problem with this goal programming model. Recommender systems suggest relevant items to users by acqui...
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| Vydáno v: | Journal of computational science Ročník 28; s. 43 - 50 |
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| Hlavní autoři: | , , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
| Vydáno: |
Elsevier B.V
01.09.2018
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| ISSN: | 1877-7503, 1877-7511 |
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| Abstract | •Combining content information of movie features with collaborative filtering approach.•Using a goal programming model in the content-based method to predict missing ratings.•Overcome data sparsity problem with this goal programming model.
Recommender systems suggest relevant items to users by acquiring user preferences and exploiting them to build a type of user model. The main purpose of such a system is to match the most suitable item for the constructed user model. And hence, finding similar items for user preferences is the most crucial point of any recommender system. The state-of-art recommender systems suffer from handling the data sparsity problem. For this reason, the proposed recommender system combines content information of movie features (cast, director, genre, etc.) with a collaborative filtering approach. The similarity scores of movie features are supplemented by a goal programming model in the content-based approach. Pearson correlation is selected as a collaborative filtering algorithm that predicts movies to satisfy user tastes considering the content-based similarity scores. MovieLens dataset is used for experimental setup and Mean Absolute Error is measured for the comparison of approaches. The best average MAE score is 0.736 when the evaluation includes 300 training users. Also, the fastest sub-task is the movie recommendation for users having 2.34 s running time. The proposed system outperforms the rest of the studies in the literature and the experiments show that the overall system performance is increased when the content information is augmented by the collaborative filtering approach. |
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| AbstractList | •Combining content information of movie features with collaborative filtering approach.•Using a goal programming model in the content-based method to predict missing ratings.•Overcome data sparsity problem with this goal programming model.
Recommender systems suggest relevant items to users by acquiring user preferences and exploiting them to build a type of user model. The main purpose of such a system is to match the most suitable item for the constructed user model. And hence, finding similar items for user preferences is the most crucial point of any recommender system. The state-of-art recommender systems suffer from handling the data sparsity problem. For this reason, the proposed recommender system combines content information of movie features (cast, director, genre, etc.) with a collaborative filtering approach. The similarity scores of movie features are supplemented by a goal programming model in the content-based approach. Pearson correlation is selected as a collaborative filtering algorithm that predicts movies to satisfy user tastes considering the content-based similarity scores. MovieLens dataset is used for experimental setup and Mean Absolute Error is measured for the comparison of approaches. The best average MAE score is 0.736 when the evaluation includes 300 training users. Also, the fastest sub-task is the movie recommendation for users having 2.34 s running time. The proposed system outperforms the rest of the studies in the literature and the experiments show that the overall system performance is increased when the content information is augmented by the collaborative filtering approach. |
| Author | Tekbacak, Fatih Ozturk, Cemalettin Inan, Emrah |
| Author_xml | – sequence: 1 givenname: Emrah surname: Inan fullname: Inan, Emrah email: emrah.inan@ege.edu.tr organization: Department of Computer Engineering Ege University, Izmir, Turkey – sequence: 2 givenname: Fatih surname: Tekbacak fullname: Tekbacak, Fatih email: ftekbacak@adu.edu.tr organization: Adnan Menderes University, Aydin, Turkey – sequence: 3 givenname: Cemalettin surname: Ozturk fullname: Ozturk, Cemalettin email: OzturkC@utrc.utc.com organization: United Technologies Research Center, Cork, Ireland |
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| Cites_doi | 10.1016/j.cosrev.2016.05.002 10.1109/TPAMI.2016.2608901 10.1016/0196-6774(80)90002-4 10.1016/j.knosys.2018.04.008 10.1093/comjnl/bxr001 10.1007/s10994-008-5068-4 10.1007/s11042-014-1950-1 10.1023/A:1021240730564 10.1109/TNNLS.2018.2817538 10.1007/BF02579150 10.1023/A:1011419012209 10.1145/1278366.1278372 10.1109/TNNLS.2016.2582746 10.1145/245108.245124 10.1109/TCYB.2016.2539546 10.1109/MIC.2003.1167344 10.1109/TKDE.2017.2728531 10.1109/TIP.2017.2708506 |
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| Keywords | Content-based recommender systems Collaborative filtering Recommender systems Goal programming |
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| References | Luo, Niu, Shen, Ullrich (bib0090) 2008; 72 Ziegler, McNee, Konstan, Lausen (bib0030) 2005 Özbal, Karaman, Alpaslan (bib0035) 2011; 54 Spiegel, Kunegis, Li (bib0105) 2009 Elhoseny, Shehab, Osman (bib0130) 2018 Sarker, Newton (bib0165) 2007 Xue, Lin, Yang, Xi, Zeng, Yu, Chen (bib0095) 2005 Li, Nie, Chang, Yang (bib0160) 2017; 29 Linden, Smith, York (bib0025) 2003; 7 Chang, Yang (bib0150) 2017; 28 Ma, King, Lyu (bib0040) 2007 Chang, Ma, Lin, Yang, Hauptmann (bib0140) 2017; 26 Ortega, Zhu, Bobadilla, Hernando (bib0195) 2018; 152 Su, Khoshgoftaar (bib0005) 2009; 2009 Ahn, Shi (bib0065) 2009 Schafer, Konstan, Riedl (bib0015) 2001 Debnath, Ganguly, Mitra (bib0060) 2008 Soares, Viana (bib0070) 2015; 74 Fayyad, Piatetsky-Shapiro, Smyth (bib0010) 1996; 17 Shardanand, Maes (bib0075) 1995 Yuan, Li, Mohapatra, Elhoseny (bib0125) 2017 Li, Nie, Chang, Nie, Zhang, Yang (bib0200) 2018 Chang, Yu, Yang, Xing (bib0155) 2017; 39 Shehab, Elhoseny, El Aziz, Hassanien (bib0135) 2018 Balabanović, Shoham (bib0110) 1997; 40 Burke (bib0055) 2002; 12 Melville, Mooney, Nagarajan (bib0100) 2002 Taha (bib0175) 2007; vol. 557 Winston, Goldberg (bib0170) 2004; vol. 3 Wang, de Vries, Reinders (bib0190) 2006 Mahmood, Ricci (bib0045) 2009 Mobasher, Burke, Bhaumik, Williams (bib0050) 2007; 7 Gunawardana, Meek (bib0115) 2009 Abdeldaim, Sahlol, Elhoseny, Hassanien (bib0120) 2018 Chang, Ma, Yang, Zeng, Hauptmann (bib0145) 2017; 47 Elahi, Ricci, Rubens (bib0080) 2016; 20 Aspvall, Stone (bib0185) 1980; 1 Goldberg, Roeder, Gupta, Perkins, Eigentaste (bib0085) 2001; 4 Fleder, Hosanagar (bib0020) 2007 Karmarkar (bib0180) 1984; 4 Li (10.1016/j.jocs.2018.08.004_bib0200) 2018 Özbal (10.1016/j.jocs.2018.08.004_bib0035) 2011; 54 Chang (10.1016/j.jocs.2018.08.004_bib0145) 2017; 47 Mahmood (10.1016/j.jocs.2018.08.004_bib0045) 2009 Schafer (10.1016/j.jocs.2018.08.004_bib0015) 2001 Abdeldaim (10.1016/j.jocs.2018.08.004_bib0120) 2018 Winston (10.1016/j.jocs.2018.08.004_bib0170) 2004; vol. 3 Spiegel (10.1016/j.jocs.2018.08.004_bib0105) 2009 Gunawardana (10.1016/j.jocs.2018.08.004_bib0115) 2009 Chang (10.1016/j.jocs.2018.08.004_bib0155) 2017; 39 Burke (10.1016/j.jocs.2018.08.004_bib0055) 2002; 12 Li (10.1016/j.jocs.2018.08.004_bib0160) 2017; 29 Elahi (10.1016/j.jocs.2018.08.004_bib0080) 2016; 20 Taha (10.1016/j.jocs.2018.08.004_bib0175) 2007; vol. 557 Karmarkar (10.1016/j.jocs.2018.08.004_bib0180) 1984; 4 Sarker (10.1016/j.jocs.2018.08.004_bib0165) 2007 Aspvall (10.1016/j.jocs.2018.08.004_bib0185) 1980; 1 Balabanović (10.1016/j.jocs.2018.08.004_bib0110) 1997; 40 Soares (10.1016/j.jocs.2018.08.004_bib0070) 2015; 74 Shardanand (10.1016/j.jocs.2018.08.004_bib0075) 1995 Ahn (10.1016/j.jocs.2018.08.004_bib0065) 2009 Chang (10.1016/j.jocs.2018.08.004_bib0150) 2017; 28 Wang (10.1016/j.jocs.2018.08.004_bib0190) 2006 Fleder (10.1016/j.jocs.2018.08.004_bib0020) 2007 Elhoseny (10.1016/j.jocs.2018.08.004_bib0130) 2018 Ortega (10.1016/j.jocs.2018.08.004_bib0195) 2018; 152 Linden (10.1016/j.jocs.2018.08.004_bib0025) 2003; 7 Melville (10.1016/j.jocs.2018.08.004_bib0100) 2002 Su (10.1016/j.jocs.2018.08.004_bib0005) 2009; 2009 Luo (10.1016/j.jocs.2018.08.004_bib0090) 2008; 72 Ziegler (10.1016/j.jocs.2018.08.004_bib0030) 2005 Debnath (10.1016/j.jocs.2018.08.004_bib0060) 2008 Fayyad (10.1016/j.jocs.2018.08.004_bib0010) 1996; 17 Ma (10.1016/j.jocs.2018.08.004_bib0040) 2007 Xue (10.1016/j.jocs.2018.08.004_bib0095) 2005 Shehab (10.1016/j.jocs.2018.08.004_bib0135) 2018 Yuan (10.1016/j.jocs.2018.08.004_bib0125) 2017 Chang (10.1016/j.jocs.2018.08.004_bib0140) 2017; 26 Mobasher (10.1016/j.jocs.2018.08.004_bib0050) 2007; 7 Goldberg (10.1016/j.jocs.2018.08.004_bib0085) 2001; 4 |
| References_xml | – start-page: 252 year: 2018 end-page: 263 ident: bib0130 article-title: An empirical analysis of user behavior for p2p iptv workloads publication-title: International Conference on Advanced Machine Learning Technologies and Applications – volume: 47 start-page: 1180 year: 2017 end-page: 1197 ident: bib0145 article-title: Bi-level semantic representation analysis for multimedia event detection publication-title: IEEE Trans. Cybern. – year: 2018 ident: bib0200 article-title: Rank-constrained spectral clustering with flexible embedding publication-title: IEEE Trans. Neural Netw. Learn. Syst. – start-page: 114 year: 2005 end-page: 121 ident: bib0095 article-title: Scalable collaborative filtering using cluster-based smoothing publication-title: Proceedings of the 28th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval – start-page: 131 year: 2018 end-page: 147 ident: bib0120 article-title: Computer-aided acute lymphoblastic leukemia diagnosis system based on image analysis publication-title: Advances in Soft Computing and Machine Learning in Image Processing – volume: 39 start-page: 1617 year: 2017 end-page: 1632 ident: bib0155 article-title: Semantic pooling for complex event analysis in untrimmed videos publication-title: IEEE Trans. Pattern Anal. Mach. Intell. – volume: 152 start-page: 94 year: 2018 end-page: 99 ident: bib0195 article-title: Cf4j: collaborative filtering for java publication-title: Knowl.-Based Syst. – volume: 2009 start-page: 4 year: 2009 ident: bib0005 article-title: A survey of collaborative filtering techniques publication-title: Adv. Artif. Intell. – start-page: 210 year: 1995 end-page: 217 ident: bib0075 article-title: Social information filtering: algorithms for automating “word of mouth” publication-title: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems – volume: 17 start-page: 37 year: 1996 ident: bib0010 article-title: From data mining to knowledge discovery in databases publication-title: AI Mag. – start-page: 477 year: 2018 end-page: 495 ident: bib0135 article-title: Efficient schemes for playout latency reduction in p2p-vod systems publication-title: Advances in Soft Computing and Machine Learning in Image Processing – year: 2007 ident: bib0165 article-title: Optimization Modelling: A Practical Approach – volume: 20 start-page: 29 year: 2016 end-page: 50 ident: bib0080 article-title: A survey of active learning in collaborative filtering recommender systems publication-title: Comput. Sci. Rev. – volume: vol. 3 year: 2004 ident: bib0170 publication-title: Operations Research: Applications and Algorithms – volume: 29 start-page: 2100 year: 2017 end-page: 2110 ident: bib0160 article-title: Beyond trace ratio: weighted harmonic mean of trace ratios for multiclass discriminant analysis publication-title: IEEE Trans. Knowl. Data Eng. – volume: vol. 557 year: 2007 ident: bib0175 publication-title: Operations Research: An Introduction – year: 2017 ident: bib0125 article-title: Automatic removal of complex shadows from indoor videos using transfer learning and dynamic thresholding publication-title: Comput. Electr. Eng. – volume: 26 start-page: 3911 year: 2017 end-page: 3920 ident: bib0140 article-title: Feature interaction augmented sparse learning for fast kinect motion detection publication-title: IEEE Trans. Image Process. – volume: 4 start-page: 133 year: 2001 end-page: 151 ident: bib0085 article-title: A constant time collaborative filtering algorithm publication-title: Inf. Retriev. – volume: 1 start-page: 1 year: 1980 end-page: 13 ident: bib0185 article-title: Khachiyan's linear programming algorithm publication-title: J. Algorithms – start-page: 501 year: 2006 end-page: 508 ident: bib0190 article-title: Unifying user-based and item-based collaborative filtering approaches by similarity fusion publication-title: Proceedings of the 29th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR ‘06 – volume: 12 start-page: 331 year: 2002 end-page: 370 ident: bib0055 article-title: Hybrid recommender systems: survey and experiments publication-title: User Model. User-Adapt. Interact. – volume: 54 start-page: 1535 year: 2011 end-page: 1546 ident: bib0035 article-title: A content-boosted collaborative filtering approach for movie recommendation based on local and global similarity and missing data prediction publication-title: Comput. J. – start-page: 39 year: 2007 end-page: 46 ident: bib0040 article-title: Effective missing data prediction for collaborative filtering publication-title: Proceedings of the 30th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval – volume: 40 start-page: 66 year: 1997 end-page: 72 ident: bib0110 article-title: Fab: content-based, collaborative recommendation publication-title: Commun. ACM – start-page: 192 year: 2007 end-page: 199 ident: bib0020 article-title: Recommender systems and their impact on sales diversity publication-title: Proceedings of the 8th ACM Conference on Electronic Commerce – start-page: 22 year: 2005 end-page: 32 ident: bib0030 article-title: Improving recommendation lists through topic diversification publication-title: Proceedings of the 14th International Conference on World Wide Web – volume: 7 start-page: 76 year: 2003 end-page: 80 ident: bib0025 article-title: Amazon. com recommendations: item-to-item collaborative filtering publication-title: IEEE Internet Comput. – start-page: 115 year: 2001 end-page: 153 ident: bib0015 article-title: E-commerce recommendation applications publication-title: Applications of Data Mining to Electronic Commerce – volume: 28 start-page: 2294 year: 2017 end-page: 2305 ident: bib0150 article-title: Semisupervised feature analysis by mining correlations among multiple tasks publication-title: IEEE Trans. Neural Netw. Learn. Syst. – volume: 4 start-page: 373 year: 1984 end-page: 395 ident: bib0180 article-title: A new polynomial-time algorithm for linear programming publication-title: Combinatorica – start-page: 119 year: 2009 end-page: 134 ident: bib0065 article-title: Exploring movie recommendation system using cultural metadata publication-title: Transactions on Edutainment II – start-page: 73 year: 2009 end-page: 82 ident: bib0045 article-title: Improving recommender systems with adaptive conversational strategies publication-title: Proceedings of the 20th ACM Conference on Hypertext and Hypermedia – volume: 74 start-page: 7015 year: 2015 end-page: 7036 ident: bib0070 article-title: Tuning metadata for better movie content-based recommendation systems publication-title: Multimed. Tools Appl. – start-page: 187 year: 2002 end-page: 192 ident: bib0100 article-title: Content-boosted collaborative filtering for improved recommendations publication-title: Aaai/iaai – start-page: 117 year: 2009 end-page: 124 ident: bib0115 article-title: A unified approach to building hybrid recommender systems publication-title: Proceedings of the Third ACM Conference on Recommender Systems – volume: 72 start-page: 231 year: 2008 end-page: 245 ident: bib0090 article-title: A collaborative filtering framework based on both local user similarity and global user similarity publication-title: Mach. Learn. – volume: 7 start-page: 23 year: 2007 ident: bib0050 article-title: Toward trustworthy recommender systems: an analysis of attack models and algorithm robustness publication-title: ACM Trans. Internet Technol. (TOIT) – start-page: 1041 year: 2008 end-page: 1042 ident: bib0060 article-title: Feature weighting in content based recommendation system using social network analysis publication-title: Proceedings of the 17th International Conference on World Wide Web – start-page: 75 year: 2009 end-page: 80 ident: bib0105 article-title: Hydra: a hybrid recommender system [cross-linked rating and content information] publication-title: Proceedings of the 1st ACM International Workshop on Complex Networks Meet Information & Knowledge Management – volume: 20 start-page: 29 issue: C year: 2016 ident: 10.1016/j.jocs.2018.08.004_bib0080 article-title: A survey of active learning in collaborative filtering recommender systems publication-title: Comput. Sci. Rev. doi: 10.1016/j.cosrev.2016.05.002 – volume: 39 start-page: 1617 issue: 8 year: 2017 ident: 10.1016/j.jocs.2018.08.004_bib0155 article-title: Semantic pooling for complex event analysis in untrimmed videos publication-title: IEEE Trans. Pattern Anal. Mach. Intell. doi: 10.1109/TPAMI.2016.2608901 – start-page: 22 year: 2005 ident: 10.1016/j.jocs.2018.08.004_bib0030 article-title: Improving recommendation lists through topic diversification – start-page: 131 year: 2018 ident: 10.1016/j.jocs.2018.08.004_bib0120 article-title: Computer-aided acute lymphoblastic leukemia diagnosis system based on image analysis – volume: 1 start-page: 1 issue: 1 year: 1980 ident: 10.1016/j.jocs.2018.08.004_bib0185 article-title: Khachiyan's linear programming algorithm publication-title: J. Algorithms doi: 10.1016/0196-6774(80)90002-4 – volume: 152 start-page: 94 year: 2018 ident: 10.1016/j.jocs.2018.08.004_bib0195 article-title: Cf4j: collaborative filtering for java publication-title: Knowl.-Based Syst. doi: 10.1016/j.knosys.2018.04.008 – volume: 17 start-page: 37 issue: 3 year: 1996 ident: 10.1016/j.jocs.2018.08.004_bib0010 article-title: From data mining to knowledge discovery in databases publication-title: AI Mag. – start-page: 501 year: 2006 ident: 10.1016/j.jocs.2018.08.004_bib0190 article-title: Unifying user-based and item-based collaborative filtering approaches by similarity fusion – volume: 54 start-page: 1535 issue: 9 year: 2011 ident: 10.1016/j.jocs.2018.08.004_bib0035 article-title: A content-boosted collaborative filtering approach for movie recommendation based on local and global similarity and missing data prediction publication-title: Comput. J. doi: 10.1093/comjnl/bxr001 – volume: 72 start-page: 231 issue: 3 year: 2008 ident: 10.1016/j.jocs.2018.08.004_bib0090 article-title: A collaborative filtering framework based on both local user similarity and global user similarity publication-title: Mach. Learn. doi: 10.1007/s10994-008-5068-4 – start-page: 114 year: 2005 ident: 10.1016/j.jocs.2018.08.004_bib0095 article-title: Scalable collaborative filtering using cluster-based smoothing – start-page: 119 year: 2009 ident: 10.1016/j.jocs.2018.08.004_bib0065 article-title: Exploring movie recommendation system using cultural metadata – volume: vol. 557 year: 2007 ident: 10.1016/j.jocs.2018.08.004_bib0175 – volume: 74 start-page: 7015 issue: 17 year: 2015 ident: 10.1016/j.jocs.2018.08.004_bib0070 article-title: Tuning metadata for better movie content-based recommendation systems publication-title: Multimed. Tools Appl. doi: 10.1007/s11042-014-1950-1 – volume: 12 start-page: 331 issue: 4 year: 2002 ident: 10.1016/j.jocs.2018.08.004_bib0055 article-title: Hybrid recommender systems: survey and experiments publication-title: User Model. User-Adapt. Interact. doi: 10.1023/A:1021240730564 – start-page: 1041 year: 2008 ident: 10.1016/j.jocs.2018.08.004_bib0060 article-title: Feature weighting in content based recommendation system using social network analysis – start-page: 117 year: 2009 ident: 10.1016/j.jocs.2018.08.004_bib0115 article-title: A unified approach to building hybrid recommender systems – start-page: 73 year: 2009 ident: 10.1016/j.jocs.2018.08.004_bib0045 article-title: Improving recommender systems with adaptive conversational strategies – start-page: 477 year: 2018 ident: 10.1016/j.jocs.2018.08.004_bib0135 article-title: Efficient schemes for playout latency reduction in p2p-vod systems – start-page: 39 year: 2007 ident: 10.1016/j.jocs.2018.08.004_bib0040 article-title: Effective missing data prediction for collaborative filtering – year: 2007 ident: 10.1016/j.jocs.2018.08.004_bib0165 – volume: vol. 3 year: 2004 ident: 10.1016/j.jocs.2018.08.004_bib0170 – year: 2018 ident: 10.1016/j.jocs.2018.08.004_bib0200 article-title: Rank-constrained spectral clustering with flexible embedding publication-title: IEEE Trans. Neural Netw. Learn. Syst. doi: 10.1109/TNNLS.2018.2817538 – volume: 2009 start-page: 4 year: 2009 ident: 10.1016/j.jocs.2018.08.004_bib0005 article-title: A survey of collaborative filtering techniques publication-title: Adv. Artif. Intell. – start-page: 115 year: 2001 ident: 10.1016/j.jocs.2018.08.004_bib0015 article-title: E-commerce recommendation applications – start-page: 192 year: 2007 ident: 10.1016/j.jocs.2018.08.004_bib0020 article-title: Recommender systems and their impact on sales diversity – volume: 4 start-page: 373 issue: 4 year: 1984 ident: 10.1016/j.jocs.2018.08.004_bib0180 article-title: A new polynomial-time algorithm for linear programming publication-title: Combinatorica doi: 10.1007/BF02579150 – start-page: 210 year: 1995 ident: 10.1016/j.jocs.2018.08.004_bib0075 article-title: Social information filtering: algorithms for automating “word of mouth” – volume: 4 start-page: 133 issue: 2 year: 2001 ident: 10.1016/j.jocs.2018.08.004_bib0085 article-title: A constant time collaborative filtering algorithm publication-title: Inf. Retriev. doi: 10.1023/A:1011419012209 – start-page: 75 year: 2009 ident: 10.1016/j.jocs.2018.08.004_bib0105 article-title: Hydra: a hybrid recommender system [cross-linked rating and content information] – volume: 7 start-page: 23 issue: 4 year: 2007 ident: 10.1016/j.jocs.2018.08.004_bib0050 article-title: Toward trustworthy recommender systems: an analysis of attack models and algorithm robustness publication-title: ACM Trans. Internet Technol. (TOIT) doi: 10.1145/1278366.1278372 – start-page: 252 year: 2018 ident: 10.1016/j.jocs.2018.08.004_bib0130 article-title: An empirical analysis of user behavior for p2p iptv workloads – volume: 28 start-page: 2294 issue: 10 year: 2017 ident: 10.1016/j.jocs.2018.08.004_bib0150 article-title: Semisupervised feature analysis by mining correlations among multiple tasks publication-title: IEEE Trans. Neural Netw. Learn. Syst. doi: 10.1109/TNNLS.2016.2582746 – volume: 40 start-page: 66 issue: 3 year: 1997 ident: 10.1016/j.jocs.2018.08.004_bib0110 article-title: Fab: content-based, collaborative recommendation publication-title: Commun. ACM doi: 10.1145/245108.245124 – year: 2017 ident: 10.1016/j.jocs.2018.08.004_bib0125 article-title: Automatic removal of complex shadows from indoor videos using transfer learning and dynamic thresholding publication-title: Comput. Electr. Eng. – volume: 47 start-page: 1180 issue: 5 year: 2017 ident: 10.1016/j.jocs.2018.08.004_bib0145 article-title: Bi-level semantic representation analysis for multimedia event detection publication-title: IEEE Trans. Cybern. doi: 10.1109/TCYB.2016.2539546 – volume: 7 start-page: 76 issue: 1 year: 2003 ident: 10.1016/j.jocs.2018.08.004_bib0025 article-title: Amazon. com recommendations: item-to-item collaborative filtering publication-title: IEEE Internet Comput. doi: 10.1109/MIC.2003.1167344 – volume: 29 start-page: 2100 issue: 10 year: 2017 ident: 10.1016/j.jocs.2018.08.004_bib0160 article-title: Beyond trace ratio: weighted harmonic mean of trace ratios for multiclass discriminant analysis publication-title: IEEE Trans. Knowl. Data Eng. doi: 10.1109/TKDE.2017.2728531 – start-page: 187 year: 2002 ident: 10.1016/j.jocs.2018.08.004_bib0100 article-title: Content-boosted collaborative filtering for improved recommendations – volume: 26 start-page: 3911 issue: 8 year: 2017 ident: 10.1016/j.jocs.2018.08.004_bib0140 article-title: Feature interaction augmented sparse learning for fast kinect motion detection publication-title: IEEE Trans. Image Process. doi: 10.1109/TIP.2017.2708506 |
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| Snippet | •Combining content information of movie features with collaborative filtering approach.•Using a goal programming model in the content-based method to predict... |
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| SubjectTerms | Collaborative filtering Content-based recommender systems Goal programming Recommender systems |
| Title | Moreopt: A goal programming based movie recommender system |
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