{"id":"W2555193411","doi":"","title":"Time Preference aware Dynamic Recommendation Enhanced with Location, Social Network and Temporal Information","year":2016,"lang":"en","type":"article","venue":"OpenMETU (Middle East Technical University)","topic":"Recommender Systems and Techniques","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science; Recommender system; Preference; Friendship; Point of interest; Point (geometry); Social network (sociolinguistics); Information retrieval; World Wide Web; Data mining; Social media; Artificial intelligence","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006550408,0.0007348288,0.00137924,0.001376236,0.0006400415,0.000931053,0.001339566,0.0009184268,0.001697731],"category_scores_gemma":[0.001761653,0.0004668274,0.001112503,0.002526092,0.0001906737,0.001977434,0.0005644974,0.0007687305,0.0008733956],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006741632,"about_ca_system_score_gemma":0.0006645312,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02878397,"about_ca_topic_score_gemma":0.04183562,"domain_scores_codex":[0.9991915,0.0001220751,0.00005705058,0.0002448438,0.0003002147,0.00008444131],"domain_scores_gemma":[0.999042,0.0003145335,0.0001033009,0.0001615101,0.000320261,0.00005844746],"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":[0.0006629085,0.0008679978,0.01734068,0.0004522616,0.0007291347,0.000827832,0.0003827683,0.2482245,0.03080595,0.01000657,0.01445262,0.6752468],"study_design_scores_gemma":[0.00002501054,0.0001244766,0.00308466,0.00001428037,0.0001458168,0.0003038794,0.00005469738,0.9886733,0.002634164,0.001553392,0.003340795,0.00004543125],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09626783,0.002790653,0.8910834,0.0004729173,0.000205822,0.000136692,0.0007999858,0.00143617,0.006806516],"genre_scores_gemma":[0.7647469,0.001645577,0.2217001,0.0001719803,0.0001773554,0.0001364213,0.001227541,0.00008184739,0.01011237],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02878397,"threshold_uncertainty_score":0.05723286,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02034860211846255,"score_gpt":0.1986574831224988,"score_spread":0.1783088810040362,"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."}}