{"id":"W2515155379","doi":"10.1145/2948065","title":"Trip Recommendation Meets Real-World Constraints","year":2016,"lang":"en","type":"article","venue":"ACM Transactions on Information Systems","topic":"Recommender Systems and Techniques","field":"Computer Science","cited_by":44,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"Higher Education Discipline Innovation Project; Natural Sciences and Engineering Research Council of Canada; Renmin University of China","keywords":"Computer science; Constraint (computer-aided design); Time constraint; Point of interest; Window (computing); Recommender system; Sequence (biology); Space (punctuation); Budget constraint; Diversity (politics); Information retrieval; World Wide Web; Operations research; Artificial intelligence; Mathematics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006893767,0.0001875872,0.0002276452,0.0005881166,0.0002368856,0.000333485,0.0006933053,0.0001017456,0.0001091471],"category_scores_gemma":[0.0000256477,0.0001332523,0.00009800099,0.0004892519,0.00003925662,0.003943333,0.000014382,0.0001105115,0.0005129232],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002464704,"about_ca_system_score_gemma":0.00006521698,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002186086,"about_ca_topic_score_gemma":0.00003131346,"domain_scores_codex":[0.9982705,0.0001443006,0.0008091913,0.0002112254,0.0003077891,0.0002569925],"domain_scores_gemma":[0.9982381,0.0002491823,0.0003394988,0.0008714289,0.000185855,0.0001158804],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001011512,0.00003950637,0.000065095,0.00004169228,0.00004500111,6.191891e-7,0.000515266,0.00002946373,0.00009997626,0.05064901,0.005527102,0.9429771],"study_design_scores_gemma":[0.001996115,0.0002765578,0.000793371,0.0004976246,0.00001700156,0.00009589107,0.0003858313,0.00359376,0.007725099,0.001563773,0.9823305,0.0007244609],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0001116949,0.000003990447,0.9591326,0.004507916,0.001679896,0.0005245631,0.00004293225,0.0007375797,0.03325889],"genre_scores_gemma":[0.9904534,0.00007778817,0.008087637,0.0002666987,0.00004822707,0.0002539471,0.00001129793,0.000009044213,0.0007919598],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9903417,"threshold_uncertainty_score":0.6592761,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03009037711056764,"score_gpt":0.2725916044633616,"score_spread":0.242501227352794,"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."}}