{"id":"W1987209614","doi":"10.5539/cis.v1n3p66","title":"Similarity Matrix Based Session Clustering by Sequence Alignment Using Dynamic Programming","year":2008,"lang":"en","type":"article","venue":"Computer and Information Science","topic":"Data Stream Mining Techniques","field":"Computer Science","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Session (web analytics); Cluster analysis; Web mining; Hierarchical clustering; Similarity (geometry); Information retrieval; World Wide Web; Data mining; Web service; Database transaction; Database; Machine learning; Artificial intelligence","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006286242,0.0001408264,0.0001205995,0.0002613653,0.0006340848,0.0006123243,0.00100918,0.00004097265,0.000001455099],"category_scores_gemma":[0.00002457682,0.0001292097,0.00002207926,0.0007589436,0.0003081737,0.01196691,0.0008313759,0.00009755168,0.000005269139],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001427843,"about_ca_system_score_gemma":0.0001873236,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002011408,"about_ca_topic_score_gemma":3.760111e-7,"domain_scores_codex":[0.9984856,0.00002547719,0.0003209921,0.0002943921,0.0005536184,0.0003199572],"domain_scores_gemma":[0.9990703,0.00003316028,0.0001645633,0.0004556395,0.0001391525,0.0001371513],"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":[0.00001543153,0.0001426008,0.004360162,0.0002096214,0.00001155599,0.00002520734,0.006519045,0.008038232,0.0167491,0.00447548,0.003129068,0.9563245],"study_design_scores_gemma":[0.0001376111,0.00006310888,0.000728023,0.00005426959,0.000001378113,0.00009435558,0.00001049434,0.9931558,0.002857493,0.00004037118,0.002687409,0.0001696909],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.05489187,0.00001518424,0.9441991,0.0001299161,0.0001633579,0.0001862348,0.000007784341,0.0003072061,0.00009933286],"genre_scores_gemma":[0.4476018,0.00001454107,0.5519803,0.0003784171,0.000006840555,0.000005199009,0.000009222585,0.000002003356,0.000001725927],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9851176,"threshold_uncertainty_score":0.8675723,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03168089812779665,"score_gpt":0.3087568984440514,"score_spread":0.2770760003162547,"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."}}