{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003106576,0.0001000339,0.0001344823,0.00004306807,0.0003735964,0.0005952599,0.0008222482,0.00005125985,0.00008208543],"category_scores_gemma":[0.00002549308,0.00008093751,0.00007108198,0.00002046391,0.00003133333,0.001001848,0.0002402215,0.0000494383,0.00001503969],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003649262,"about_ca_system_score_gemma":0.00001877657,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002021891,"about_ca_topic_score_gemma":0.0001253915,"domain_scores_codex":[0.9992855,0.00003763318,0.0001607213,0.0002746157,0.00007805931,0.0001634375],"domain_scores_gemma":[0.9991915,0.00004496213,0.0001701028,0.0004605639,0.00009000134,0.00004291623],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00003361464,0.00005485333,0.0003571134,0.0000191454,0.00007883435,0.000001405977,0.000986942,0.000001058459,0.0007871662,0.6862911,0.03150173,0.279887],"study_design_scores_gemma":[0.002169569,0.0006516071,0.0009528759,0.00007744646,0.00002161013,0.00002852516,0.000394293,0.2507368,0.07651194,0.03756612,0.6301128,0.0007763965],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0003960298,0.00001357691,0.9792157,0.003554688,0.0006166003,0.0003266617,0.000002067444,0.0001958537,0.01567878],"genre_scores_gemma":[0.6974918,0.000008370946,0.2982613,0.000243142,0.0001046692,0.0001147429,0.000004005885,0.000008635238,0.003763325],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6970958,"threshold_uncertainty_score":0.5740105,"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."}}