{"id":"W143476799","doi":"10.1007/978-3-642-30353-1_22","title":"A Study of Recommending Locations on Location-Based Social Network by Collaborative Filtering","year":2012,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Recommender Systems and Techniques","field":"Computer Science","cited_by":57,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science; Probabilistic latent semantic analysis; Collaborative filtering; Recommender system; Information retrieval; Web crawler; Set (abstract data type); Data mining; Probabilistic logic; Topic model; World Wide Web; 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":[0.003958465,0.0009741093,0.00212494,0.002977492,0.001803832,0.003116632,0.003649748,0.003214485,0.002816384],"category_scores_gemma":[0.0238714,0.001301912,0.002273771,0.006682458,0.001940621,0.008327513,0.001262902,0.001854578,0.0004799368],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002081534,"about_ca_system_score_gemma":0.001002672,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02489909,"about_ca_topic_score_gemma":0.01257908,"domain_scores_codex":[0.9972467,0.001215396,0.0001288708,0.0007285454,0.0004872315,0.0001932837],"domain_scores_gemma":[0.961813,0.03311327,0.001355408,0.001432226,0.001739659,0.0005464551],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0006726768,0.00114494,0.05174721,0.001729214,0.001524657,0.002008549,0.004088708,0.4464172,0.006290779,0.3521506,0.008293254,0.1239322],"study_design_scores_gemma":[0.00003069291,0.0001843667,0.003751237,0.00005069379,0.0001642598,0.0003226741,0.0002442937,0.9688659,0.000495245,0.02410722,0.001735066,0.00004832735],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.392474,0.009906352,0.5834042,0.00207269,0.0002586591,0.0002387039,0.0003684563,0.0001946631,0.01108219],"genre_scores_gemma":[0.8932944,0.004475039,0.09273872,0.0001579415,0.00057414,0.0001047952,0.0004311908,0.00007729069,0.008146455],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02489909,"threshold_uncertainty_score":0.04950833,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02994610291502895,"score_gpt":0.2839481129090097,"score_spread":0.2540020099939808,"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."}}