{"id":"W2108279663","doi":"10.1145/1935826.1935840","title":"Personalizing web search using long term browsing history","year":2011,"lang":"en","type":"article","venue":"","topic":"Information Retrieval and Search Behavior","field":"Computer Science","cited_by":202,"is_retracted":false,"has_abstract":true,"ca_institutions":"Microsoft (Canada)","funders":"","keywords":"Personalization; Computer science; World Wide Web; Information retrieval; Personalized search; Term (time); Search engine; The Internet; Web navigation; Web page","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":[0.001703965,0.0007296601,0.0009830279,0.002455544,0.0004383674,0.001338206,0.0007964548,0.0008108218,0.0008602373],"category_scores_gemma":[0.008321156,0.0004371798,0.0005660871,0.001894215,0.0003633214,0.00300914,0.0007496554,0.0007996876,0.0008003337],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004991048,"about_ca_system_score_gemma":0.0005896051,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003524681,"about_ca_topic_score_gemma":0.006462081,"domain_scores_codex":[0.9990456,0.0003183555,0.00007030637,0.0002180335,0.0002722307,0.00007551222],"domain_scores_gemma":[0.9949459,0.00250618,0.0005523527,0.001178344,0.0006266639,0.0001904274],"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":[0.0009483758,0.001174658,0.06212535,0.0002886753,0.0003857808,0.0002253121,0.0009451904,0.08823214,0.03096064,0.003295026,0.004824042,0.8065948],"study_design_scores_gemma":[0.00005738419,0.0005534567,0.02564757,0.00003282253,0.0002342697,0.0007515355,0.0002005032,0.9446262,0.01548415,0.008284634,0.004004071,0.0001234658],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4846486,0.002298242,0.5024747,0.0003825342,0.00006068329,0.0002631614,0.0003915684,0.004002661,0.005477836],"genre_scores_gemma":[0.9087268,0.00061187,0.08697011,0.00006498577,0.0001211663,0.00006486169,0.0004712953,0.0001557663,0.00281308],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003524681,"threshold_uncertainty_score":0.009011507,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2027700771185297,"score_gpt":0.2961379762883247,"score_spread":0.09336789916979496,"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."}}