{"id":"W2724638838","doi":"10.1109/bigmm.2017.76","title":"Trend and Value Based Time Series Representation for Similarity Search","year":2017,"lang":"en","type":"article","venue":"","topic":"Time Series Analysis and Forecasting","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Nearest neighbor search; Preprocessor; Data mining; Similarity (geometry); Curse of dimensionality; Series (stratigraphy); Representation (politics); Transformation (genetics); Process (computing); Time series; Similarity measure; Artificial intelligence; Value (mathematics); Machine learning; Pattern recognition (psychology)","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008779458,0.0006092324,0.0008083536,0.002662475,0.0003423515,0.001204573,0.0009527485,0.0008199727,0.004084171],"category_scores_gemma":[0.005799105,0.0001844503,0.0007798694,0.005481398,0.000466012,0.002502821,0.0007699853,0.0009311461,0.0009641543],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005774964,"about_ca_system_score_gemma":0.0006847033,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002012564,"about_ca_topic_score_gemma":0.001308142,"domain_scores_codex":[0.9993014,0.0002125531,0.00008225987,0.000149464,0.0002134072,0.00004086784],"domain_scores_gemma":[0.9988157,0.0006227372,0.0001913295,0.0001746078,0.0001588211,0.00003680213],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001911275,0.0001557156,0.002840114,0.0003406299,0.000107821,0.0002419294,0.0002376044,0.2813204,0.009459076,0.2463163,0.005274703,0.4535145],"study_design_scores_gemma":[0.000008273783,0.00004268878,0.0004098418,0.00001438338,0.00001259222,0.00008309672,0.00002976768,0.9495531,0.001009618,0.04631468,0.002507522,0.00001451857],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01596719,0.0007250677,0.9806898,0.0001544386,0.00006347806,0.00005070545,0.0002989396,0.0003618484,0.001688474],"genre_scores_gemma":[0.4667122,0.001592403,0.5267116,0.0001017455,0.0001922992,0.0003410649,0.001552762,0.0001297244,0.002666091],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.004084171,"threshold_uncertainty_score":0.01366293,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04540092119491593,"score_gpt":0.3042654850254244,"score_spread":0.2588645638305084,"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."}}