{"id":"W2593509409","doi":"10.1145/3025171.3025207","title":"Deep Sequential Recommendation for Personalized Adaptive User Interfaces","year":2017,"lang":"en","type":"article","venue":"","topic":"Recommender Systems and Techniques","field":"Computer Science","cited_by":57,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Usability; Adaptation (eye); Human–computer interaction; User interface; Metric (unit); Embedding; Collaborative filtering; User modeling; Artificial intelligence; Recommender system; Machine learning","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":[0.001111098,0.0009322158,0.001189524,0.0007146581,0.0003495242,0.0005969651,0.001598192,0.0009369691,0.003029013],"category_scores_gemma":[0.003342462,0.0005105428,0.0007463415,0.001076756,0.0003749321,0.001735561,0.000624105,0.001388257,0.001536706],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001083798,"about_ca_system_score_gemma":0.0009157826,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02481105,"about_ca_topic_score_gemma":0.05282772,"domain_scores_codex":[0.9992494,0.0002005967,0.000056492,0.0002225366,0.0001841151,0.00008686978],"domain_scores_gemma":[0.9989437,0.0003859623,0.00007281517,0.0002548783,0.000287658,0.00005491133],"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":[0.0005741057,0.0005879616,0.004821887,0.0003689783,0.0002470972,0.0001688631,0.0002958488,0.2310336,0.01595118,0.009390104,0.01554296,0.7210174],"study_design_scores_gemma":[0.00001601757,0.00008769346,0.0005135923,0.000008106959,0.00002338431,0.00003865988,0.00001498102,0.9924282,0.001935915,0.003067358,0.001853184,0.00001278828],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.06315523,0.002207247,0.9246184,0.0004537894,0.0001320779,0.0001275356,0.0008503689,0.005180676,0.003274683],"genre_scores_gemma":[0.724557,0.001204787,0.2614179,0.000312269,0.0000879365,0.0001873384,0.001961754,0.000184607,0.01008633],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.02481105,"threshold_uncertainty_score":0.04933327,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07801957483650587,"score_gpt":0.3325253581861563,"score_spread":0.2545057833496503,"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."}}