{"id":"W4214909787","doi":"10.1109/imcom53663.2022.9721788","title":"Mining Contextual Item Similarity without Concept Hierarchy","year":2022,"lang":"en","type":"article","venue":"2022 16th International Conference on Ubiquitous Information Management and Communication (IMCOM)","topic":"Data Mining Algorithms and Applications","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"Natural Sciences and Engineering Research Council of Canada; University of Technology Sydney; University of Manitoba","keywords":"Computer science; Data mining; Similarity measure; Similarity (geometry); Measure (data warehouse); Metadata; Heuristic; Information retrieval; Artificial intelligence; Image (mathematics)","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006369125,0.0001994898,0.0001742697,0.000357028,0.0009874316,0.0006977066,0.002554531,0.00003971518,0.0005048865],"category_scores_gemma":[0.00003261431,0.0002203411,0.00005381063,0.0003523093,0.0001043632,0.00158418,0.002346311,0.0003817965,0.00005167197],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001468049,"about_ca_system_score_gemma":0.00005384339,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003837484,"about_ca_topic_score_gemma":0.000008210398,"domain_scores_codex":[0.9979938,0.0001705514,0.0005488129,0.0003018139,0.0007571725,0.0002278919],"domain_scores_gemma":[0.9982147,0.0001228066,0.0003828414,0.0009776468,0.0002099295,0.00009206156],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001928299,0.00007898449,0.0002151822,0.000008455189,0.00005590501,0.000001112451,0.002072723,0.0001804114,0.000005382643,0.7834553,0.009954724,0.2039525],"study_design_scores_gemma":[0.001131789,0.0001676205,0.002230801,0.00003887932,0.0000167099,0.00001798511,0.005950525,0.5098666,0.00004426305,0.008759734,0.4713683,0.0004067766],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.01741614,0.000309957,0.4696402,0.03559901,0.001642296,0.002075731,0.0005696432,0.001036343,0.4717107],"genre_scores_gemma":[0.9542199,0.0003788901,0.03590548,0.004318899,0.00004272694,0.0006697011,0.001330181,0.00001236207,0.003121875],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9368038,"threshold_uncertainty_score":0.8985248,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03522629163458004,"score_gpt":0.2831586965514843,"score_spread":0.2479324049169042,"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."}}