{"id":"W1976974399","doi":"10.1145/1188966.1188996","title":"Improving web site search using web server logs","year":2006,"lang":"en","type":"article","venue":"","topic":"Web Data Mining and Analysis","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"Natural Sciences and Engineering Research Council of Canada; Connaught Fund; University of Toronto; National University of Singapore","keywords":"Computer science; Information retrieval; Web page; Web server; Web search engine; Static web page; Web modeling; Web crawler; World Wide Web; Data Web; Ranking (information retrieval); Web mining; Search engine; Web search query; Data mining; Web navigation; The Internet","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":[0.002272723,0.0009449557,0.001604003,0.004725181,0.0004023761,0.001471742,0.001065696,0.000796327,0.0007751427],"category_scores_gemma":[0.01440307,0.0003719985,0.0006061601,0.003224566,0.0002660849,0.004375825,0.0007055734,0.0005851285,0.001011143],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000604019,"about_ca_system_score_gemma":0.001066167,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008883237,"about_ca_topic_score_gemma":0.008913928,"domain_scores_codex":[0.9984722,0.0004873262,0.0001203606,0.0001736363,0.0006344529,0.0001121724],"domain_scores_gemma":[0.995441,0.00229635,0.0004454543,0.0006995686,0.0009897951,0.0001277947],"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":[0.0009045809,0.0009403147,0.03840394,0.0003213477,0.0001812868,0.0001315067,0.0001958466,0.06987123,0.02294751,0.001258352,0.004867018,0.859977],"study_design_scores_gemma":[0.00007300281,0.000305352,0.009539477,0.00001891826,0.0001136059,0.0002322856,0.0001186398,0.9667578,0.01935996,0.001713834,0.00172559,0.00004149915],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5211599,0.001545272,0.4557044,0.0003866729,0.00006257265,0.0002868816,0.0006026431,0.01665524,0.0035965],"genre_scores_gemma":[0.8646345,0.0004852406,0.1308148,0.00006121593,0.00008858031,0.00008514341,0.001447371,0.0002332336,0.002149925],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008883237,"threshold_uncertainty_score":0.01766306,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02198109100242396,"score_gpt":0.2495210837968287,"score_spread":0.2275399927944048,"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."}}