{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003464496,0.00008624146,0.00008312507,0.0001642543,0.0001410274,0.0000743983,0.0004938373,0.00004147288,0.0007314301],"category_scores_gemma":[0.000008459514,0.00007552127,0.00005757084,0.0001781342,0.00005625793,0.001194466,0.0002079665,0.0001421345,0.0001450407],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002776762,"about_ca_system_score_gemma":0.0002467139,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001422787,"about_ca_topic_score_gemma":0.000005187818,"domain_scores_codex":[0.9989418,0.00003980206,0.0001688194,0.0001675295,0.0003722527,0.0003097797],"domain_scores_gemma":[0.9994676,0.00001603952,0.0000347646,0.0002485742,0.0001153752,0.0001176086],"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":[0.00007465025,0.0005284063,0.225904,0.0003238615,0.00008383646,0.0005145405,0.1332709,0.00003648853,0.09847894,0.2159648,0.002823489,0.3219962],"study_design_scores_gemma":[0.001537106,0.0003018356,0.2548716,0.0001795284,0.0000308626,0.0004683568,0.001150968,0.685712,0.04677493,0.0001771192,0.007253753,0.001541926],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6517931,0.0001023604,0.3043694,0.00003824197,0.0003753097,0.0001212708,4.403889e-7,0.0002130167,0.04298687],"genre_scores_gemma":[0.9450657,0.000004076597,0.05220347,0.0003158956,0.00003696734,0.000001533195,8.228051e-7,0.00000659331,0.002364992],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6856756,"threshold_uncertainty_score":0.8008647,"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."}}