{"id":"W4285328254","doi":"10.1109/csci54926.2021.00298","title":"A Review on Multiple Data Source Based Recommendation Systems","year":2021,"lang":"en","type":"review","venue":"2021 International Conference on Computational Science and Computational Intelligence (CSCI)","topic":"Recommender Systems and Techniques","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Recommender system; Computer science; Matrix decomposition; Information retrieval; Data modeling; Data source; Multimedia; Database","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","scholarly_communication","open_science"],"consensus_categories":[],"category_scores_codex":[0.003122197,0.0008542687,0.001488504,0.001125839,0.000686761,0.002283192,0.005607998,0.0002431371,0.0003369118],"category_scores_gemma":[0.001204327,0.0007578356,0.000281091,0.002141082,0.0004192845,0.001478828,0.001649798,0.0008107245,0.0002497585],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006432754,"about_ca_system_score_gemma":0.003804647,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008569728,"about_ca_topic_score_gemma":0.000007609445,"domain_scores_codex":[0.991609,0.0005979771,0.001727168,0.00276657,0.002697207,0.0006021211],"domain_scores_gemma":[0.9917238,0.002618528,0.001202805,0.001352953,0.002722684,0.0003792504],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000003932707,0.0002047836,0.000001901143,0.001313881,0.00009241304,0.00001524931,0.00002495518,0.009584506,1.156634e-7,0.166755,0.009158321,0.812845],"study_design_scores_gemma":[0.0000762141,0.0001005904,0.000002689095,0.01771515,0.00003709809,0.00008707157,0.00002584973,0.5323049,6.704136e-7,0.002185831,0.4469754,0.0004885079],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"review","genre_scores_codex":[2.62643e-7,0.4011084,0.5893898,0.002943484,0.001590173,0.001050188,0.0002895989,0.0001527112,0.003475372],"genre_scores_gemma":[0.0008862201,0.968065,0.02289208,0.003501062,0.0003691911,0.0003530644,0.003620411,0.00005402127,0.0002589264],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.8123565,"threshold_uncertainty_score":0.9997721,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2805813739448751,"score_gpt":0.4285001182690183,"score_spread":0.1479187443241433,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}