{"id":"W2079002317","doi":"10.1109/wi-iat.2010.42","title":"Comparing Tag Clouds, Term Histograms, and Term Lists for Enhancing Personalized Web Search","year":2010,"lang":"en","type":"article","venue":"","topic":"Recommender Systems and Techniques","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Personalization; Information retrieval; Term (time); Ranking (information retrieval); World Wide Web; Web page; Visualization; Tag cloud; Process (computing); Search engine; Data mining","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":[0.001852452,0.0006061306,0.0005853237,0.003321564,0.000377637,0.001711566,0.0005140883,0.0006301167,0.00164514],"category_scores_gemma":[0.009510799,0.0002800977,0.0004693524,0.003245837,0.0003266929,0.003046048,0.0007896416,0.0004567215,0.0004461218],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007026708,"about_ca_system_score_gemma":0.0006073079,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009242505,"about_ca_topic_score_gemma":0.01177236,"domain_scores_codex":[0.9992823,0.0002564212,0.00004111674,0.00008811068,0.0002671304,0.00006498677],"domain_scores_gemma":[0.9948283,0.003485916,0.000438681,0.0004948326,0.0005658634,0.0001864968],"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":[0.002569731,0.0005773936,0.01994863,0.0006254769,0.0002957041,0.0001325241,0.001093171,0.04801455,0.04405869,0.007319488,0.00430113,0.8710634],"study_design_scores_gemma":[0.000354044,0.001560695,0.05035288,0.0001081713,0.0006974156,0.0005902015,0.001255916,0.8585677,0.05772803,0.01849574,0.009935793,0.0003535605],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3862412,0.002732711,0.6011575,0.000308624,0.0001080382,0.0002431611,0.0006843982,0.004498549,0.004025925],"genre_scores_gemma":[0.755622,0.000600102,0.2419824,0.00004911582,0.00004888591,0.00007593023,0.0004487945,0.0001484733,0.001024168],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009242505,"threshold_uncertainty_score":0.01837742,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03713189864003269,"score_gpt":0.2956448293241765,"score_spread":0.2585129306841438,"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."}}