{"id":"W2884831277","doi":"10.4018/978-1-5225-2255-3.ch695","title":"An Efficient and Effective Index Structure for Query Evaluation in Search Engines","year":2017,"lang":"en","type":"book-chapter","venue":"IGI Global eBooks","topic":"Web Data Mining and Analysis","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Winnipeg","funders":"","keywords":"Inverted index; Computer science; Disjoint sets; Intersection (aeronautics); Trie; Information retrieval; Word (group theory); Set (abstract data type); Interval (graph theory); Sequence (biology); Index (typography); Data mining; Coding (social sciences); Data structure; Theoretical computer science; Search engine indexing; Mathematics; Programming language; Combinatorics; Engineering","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":[0.004295744,0.001028698,0.002400249,0.005093918,0.001985222,0.00512528,0.003030287,0.00171848,0.006146449],"category_scores_gemma":[0.01516722,0.001142227,0.001053444,0.007178782,0.001165826,0.01029122,0.00374605,0.001929752,0.004642936],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001854619,"about_ca_system_score_gemma":0.002358652,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00238147,"about_ca_topic_score_gemma":0.002996862,"domain_scores_codex":[0.9942731,0.001211121,0.0009088204,0.0005508664,0.002736049,0.000319987],"domain_scores_gemma":[0.9943467,0.002183214,0.0004015585,0.001701544,0.001195373,0.0001715483],"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":[0.0004378418,0.0003898215,0.001798738,0.001035662,0.0001464781,0.0003082525,0.0008875449,0.01322024,0.0410669,0.1125021,0.04310975,0.7850966],"study_design_scores_gemma":[0.0003295446,0.0008508777,0.002382513,0.0004961488,0.0003163601,0.002278771,0.0007870668,0.5475256,0.08094458,0.2182187,0.1455623,0.0003074626],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.008272073,0.002624439,0.9763036,0.0006177982,0.000140514,0.0007362869,0.001045114,0.006584546,0.003675532],"genre_scores_gemma":[0.04795147,0.001008257,0.944353,0.0002281731,0.0001932928,0.0005680303,0.00169995,0.000562435,0.003435293],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.006146449,"threshold_uncertainty_score":0.02271831,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02005119448670625,"score_gpt":0.3010655075254712,"score_spread":0.281014313038765,"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."}}