{"id":"W1973206570","doi":"10.1016/j.dss.2007.05.006","title":"Website browsing aid: A navigation graph-based recommendation system","year":2007,"lang":"en","type":"article","venue":"Decision Support Systems","topic":"Recommender Systems and Techniques","field":"Computer Science","cited_by":45,"is_retracted":false,"has_abstract":false,"ca_institutions":"McMaster University","funders":"China Scholarship Council; Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China; University of Washington","keywords":"Computer science; Recommender system; Information overload; Graph; World Wide Web; Navigation system; Information retrieval; Real-time computing","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005289133,0.0009631778,0.001194415,0.002957765,0.0005273045,0.0009093882,0.001204475,0.001374713,0.01252255],"category_scores_gemma":[0.002175171,0.0003378649,0.0005481048,0.001946348,0.000105676,0.001277143,0.0007540797,0.0007749887,0.008079953],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003074366,"about_ca_system_score_gemma":0.0005800743,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01114423,"about_ca_topic_score_gemma":0.02607699,"domain_scores_codex":[0.9997529,0.00004281298,0.00002215329,0.0000574251,0.0001050772,0.00001952978],"domain_scores_gemma":[0.998943,0.0003063898,0.00004822516,0.0001962191,0.0003575755,0.0001485217],"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":[0.002640546,0.001630516,0.01313125,0.0006931485,0.0004491302,0.0004807563,0.0001649308,0.004660754,0.02622485,0.001436388,0.1610543,0.7874334],"study_design_scores_gemma":[0.001591192,0.002315882,0.0353485,0.0002315609,0.002356961,0.001734686,0.0004086987,0.7342494,0.06223669,0.006493594,0.1524552,0.0005776557],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1986241,0.003302411,0.4519362,0.001689448,0.0008996316,0.002004897,0.02972585,0.2831864,0.02863109],"genre_scores_gemma":[0.3972919,0.00159865,0.5293646,0.0009130114,0.0002981044,0.0006599061,0.02470864,0.001203598,0.04396168],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01252255,"threshold_uncertainty_score":0.04189211,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02553002171818773,"score_gpt":0.291850017953823,"score_spread":0.2663199962356352,"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."}}