{"id":"W4286817176","doi":"10.1007/s41060-022-00343-y","title":"Semantic enhanced Markov model for sequential E-commerce product recommendation","year":2022,"lang":"en","type":"article","venue":"International Journal of Data Science and Analytics","topic":"Recommender Systems and Techniques","field":"Computer Science","cited_by":26,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Windsor","funders":"","keywords":"Markov chain; Stochastic matrix; Computer science; Context (archaeology); Markov model; Recommender system; Product (mathematics); Information retrieval; Data mining; Theoretical computer science; Artificial intelligence; Machine learning; Mathematics","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":[0.002070617,0.0009491773,0.002756239,0.001786076,0.0007279137,0.001501139,0.003365304,0.002380565,0.006060798],"category_scores_gemma":[0.006767632,0.001090554,0.001797485,0.002361977,0.0009454029,0.002816639,0.001098531,0.002281469,0.001484807],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001488102,"about_ca_system_score_gemma":0.001832507,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03205339,"about_ca_topic_score_gemma":0.03877445,"domain_scores_codex":[0.9988289,0.000350022,0.00009442959,0.0003366363,0.0002145142,0.0001754034],"domain_scores_gemma":[0.9945642,0.004134687,0.0003365247,0.0003292443,0.0004871314,0.0001482082],"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":[0.0005030502,0.0002328883,0.004082119,0.0002455876,0.0002588884,0.0002470089,0.0001375239,0.9043088,0.001096273,0.04508687,0.003606039,0.04019503],"study_design_scores_gemma":[0.00001282158,0.00001829532,0.0002356234,0.000007423343,0.00002461627,0.00001963627,0.000004132095,0.9922526,0.00006370481,0.007163324,0.0001889514,0.000008904597],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09253556,0.002350896,0.8961545,0.001364137,0.0002625292,0.0001249861,0.00289056,0.0009495872,0.003367274],"genre_scores_gemma":[0.9088203,0.001901123,0.07032604,0.0003612573,0.0003029906,0.0003002511,0.003369497,0.0001120337,0.01450636],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03205339,"threshold_uncertainty_score":0.06373364,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08763348725034148,"score_gpt":0.362908129229054,"score_spread":0.2752746419787125,"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."}}