{"id":"W3193171431","doi":"10.1142/s0219622021500619","title":"Pointer-Based Item-to-Item Collaborative Filtering Recommendation System Using a Machine Learning Model","year":2021,"lang":"en","type":"article","venue":"International Journal of Information Technology & Decision Making","topic":"Recommender Systems and Techniques","field":"Computer Science","cited_by":62,"is_retracted":false,"has_abstract":true,"ca_institutions":"Brandon University","funders":"Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada","keywords":"Recommender system; Computer science; Collaborative filtering; Machine learning; Artificial intelligence; Scalability; Context (archaeology); Similarity (geometry); Recall; Mean squared error; Information retrieval; Image (mathematics); Database; Mathematics; Statistics","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001450091,0.0008663252,0.002375208,0.001560099,0.001240024,0.001419323,0.002482416,0.001831524,0.004160558],"category_scores_gemma":[0.002672381,0.0005298639,0.00158342,0.002322041,0.0003890679,0.002188665,0.0006944276,0.001343045,0.003297299],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001258215,"about_ca_system_score_gemma":0.001706782,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04766257,"about_ca_topic_score_gemma":0.03995444,"domain_scores_codex":[0.9985719,0.0002011691,0.000150406,0.0004942171,0.0004590228,0.0001232088],"domain_scores_gemma":[0.9986511,0.0003206031,0.00007705158,0.0001472949,0.0007478237,0.00005613486],"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":[0.0006666884,0.0009038162,0.008698529,0.0003889011,0.0004780481,0.0005304069,0.0002557019,0.2469874,0.01217659,0.005384661,0.01500958,0.7085198],"study_design_scores_gemma":[0.00003192894,0.0001077261,0.0007689449,0.00001124908,0.00005368454,0.0001027799,0.00001778703,0.9947909,0.001695143,0.0009641686,0.001426151,0.00002970977],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.04446682,0.0009772436,0.940501,0.0006546918,0.0002377821,0.0003635592,0.0007478826,0.006208075,0.005842833],"genre_scores_gemma":[0.5383184,0.001074623,0.4383177,0.0005000007,0.000202511,0.0005009485,0.001490017,0.0001027236,0.01949308],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.04766257,"threshold_uncertainty_score":0.09477025,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01715713640805244,"score_gpt":0.307494911679278,"score_spread":0.2903377752712256,"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."}}