04372nam 2200721Ia 450 991013978910332120200520144314.01-282-29174-297866122917460-470-71245-70-470-74941-50-470-74942-3(CKB)1000000000794485(EBL)456236(OCoLC)463438684(SSID)ssj0000179078(PQKBManifestationID)11165205(PQKBTitleCode)TC0000179078(PQKBWorkID)10230289(PQKB)11344620(MiAaPQ)EBC456236(Au-PeEL)EBL456236(CaPaEBR)ebr10331490(CaONFJC)MIL229174(EXLCZ)99100000000079448520090507d2009 uy 0engur|n|---|||||txtccrInformation retrieval[electronic resource] SciFinder /Damon D. Ridley2nd ed.Hoboken, N.J. Wiley20091 online resource (228 p.)Description based upon print version of record.0-470-71247-3 Includes bibliographical references and index.3.2 How SciFinder Converts the Query to a List of Candidates3.2.1 Search Fields; 3.2.2 Candidates; 3.2.3 Notes on Terms Entered; 3.3 How Is a Concept Derived?; 3.3.1 Automatic Truncation; 3.3.2 Singulars, Plurals, Tenses (Past, Present, Future); 3.3.3 Synonyms; 3.3.4 Phrases; 3.3.5 CAS Registry Numbers; 3.4 Choosing Candidates; 3.5 Working from the Reference Screen; 3.5.1 Keep Me Posted; 3.5.2 Search History; 3.5.3 Selecting, Saving, Printing, Exporting, and Sorting Records; 3.5.4 Link to Full Record and Link to Full Text; 3.5.5 Analyze References; 3.5.6 Refine References3.5.7 Analyze or Refine?3.5.8 Categorize; 3.6 Working from the Record Screen; 3.7 Applying Scientific Method to Information Retrieval; 3.7.1 Step 1. Conceptualize the Initial Search Query; 3.7.2 Step 2. Perform an Initial Search; 3.7.3 Step 3. Examine the Initial Answers; 3.7.4 Step 4. Revise Search; 3.8 Summary of Key Points; 4 Explore by Chemical Substance; 4.1 Introduction; 4.2 Registration of Substances; 4.2.1 CAS Registry Numbers; 4.2.2 Policies for Substance Indexing; 4.3 Searching for Substances: The Alternatives; 4.4 Explore Substances: Chemical Structure; 4.4.1 Overview4.4.2 Drawing Structures4.4.3 Explore Substances: Exact search; 4.5 Explore Substances: Substance Identifier; 4.6 Explore Substances: Molecular Formula; 4.6.1 Examples of Applications of Searches by Molecular Formula; 4.7 Explore References: Research Topic; 4.8 Summary of Key Points; 5 Substructure and Similarity Searching; 5.1 Introduction; 5.2 Searching Substances: Substructure; 5.2.1 The Screening Issue; 5.2.2 Structure Is Too General; 5.2.3 The Resonance Issue; 5.2.4 The Tautomerism Issue; 5.2.5 Show Precision Analysis; 5.2.6 Locking Tools; 5.2.7 Additional Query Tools5.2.8 Additional Search RefinementsSciFinder® is rapidly becoming a preferred means to access scientific information in industry and universities worldwide. It accesses databases which span the chemical, engineering, life, medical, and physical sciences, including five Chemical Abstract Service databases and the National Library of Medicine bibliographic database Medline®. No other single information access tool has such breadth of coverage for scientific journal and patent documents. Information Retrieval: SciFinder®, 2nd Edition is an essential guide explaining hoDatabase managementInformation storage and retrieval systemsScienceOnline bibliographic searchingScienceDatabasesInformation retrievalElectronic books.Database management.Information storage and retrieval systemsScience.Online bibliographic searching.ScienceInformation retrieval.025.065Ridley D. D(Damon D.)746295MiAaPQMiAaPQMiAaPQBOOK9910139789103321Information retrieval2231747UNINA04870nam 2200505 450 99651775530331620230729144051.03-031-25599-210.1007/978-3-031-25599-1(MiAaPQ)EBC7211136(Au-PeEL)EBL7211136(CKB)26240745100041(DE-He213)978-3-031-25599-1(PPN)26909248X(EXLCZ)992624074510004120230729d2023 uy 0engurcnu||||||||txtrdacontentcrdamediacrrdacarrierMachine learning, optimization, and data science 8th international conference, LOD 2022, Certosa Di Pontignano, Italy, September 18-22, 2022, revised selected papers, Part I /Giuseppe Nicosia [and seven others], editors1st ed. 2023.Cham, Switzerland :Springer Nature Switzerland AG,[2023]©20231 online resource (639 pages)Lecture Notes in Computer Science,1611-3349 ;13810Print version: Nicosia, Giuseppe Machine Learning, Optimization, and Data Science Cham : Springer,c2023 9783031255984 Includes bibliographical references and index.Explainable Machine Learning for Drug Shortage Prediction in a Pandemic Setting -- Intelligent Robotic Process Automation for Supplier Document Management on E-Procurement Platforms -- Batch Bayesian Quadrature with Batch Updating Using Future Uncertainty Sampling -- Sensitivity analysis of Engineering Structures Utilizing Artificial Neural Networks and Polynomial -- Inferring Pathological Metabolic Patterns in Breast Cancer Tissue from Genome-Scale Models -- Deep Learning -- Machine Learning -- Reinforcement Learning -- Neural Networks -- Deep Reinforcement Learning -- Optimization -- Global Optimization -- Multi-Objective Optimization -- Computational Optimization -- Data Science -- Big Data -- Data Analytics -- Artificial Intelligence -- Detection of Morality in Tweets based on the Moral Foundation Theory -- Matrix completion for the prediction of yearly country and industry-level CO2 emissions -- A Benchmark for Real-Time Anomaly Detection Algorithms Applied in Industry 4.0 -- A Matrix Factorization-based Drug-virus Link Prediction Method for SARS CoV -- Drug Prioritization -- Hyperbolic Graph Codebooks -- A Kernel-Based Multilayer Perceptron Framework to Identify Pathways Related to Cancer Stages -- Loss Function with Memory for Trustworthiness Threshold Learning: Case of Face and Facial Expression Recognition -- Machine learning approaches for predicting Crystal Systems: a brief review and a case study -- LS-PON: a Prediction-based Local Search for Neural Architecture Search -- Local optimisation of Nystrm samples through stochastic gradient descent -- Explainable Machine Learning for Drug Shortage Prediction in a Pandemic Setting -- Intelligent Robotic Process Automation for Supplier Document Management on E-Procurement Platforms -- Batch Bayesian Quadrature with Batch Updating Using Future Uncertainty Sampling -- Sensitivity analysis of Engineering Structures Utilizing Artificial Neural Networks and Polynomial -- Inferring Pathological Metabolic Patterns in Breast Cancer Tissue from Genome-Scale Models -- Deep Learning -- Machine Learning -- Reinforcement Learning -- Neural Networks -- Deep Reinforcement Learning -- Optimization -- Global Optimization -- Multi-Objective Optimization -- Computational Optimization -- Data Science -- Big Data -- Data Analytics -- Artificial Intelligence.This two-volume set, LNCS 13810 and 13811, constitutes the refereed proceedings of the 8th International Conference on Machine Learning, Optimization, and Data Science, LOD 2022, together with the papers of the Second Symposium on Artificial Intelligence and Neuroscience, ACAIN 2022. The total of 84 full papers presented in this two-volume post-conference proceedings set was carefully reviewed and selected from 226 submissions. These research articles were written by leading scientists in the fields of machine learning, artificial intelligence, reinforcement learning, computational optimization, neuroscience, and data science presenting a substantial array of ideas, technologies, algorithms, methods, and applications.Lecture Notes in Computer Science,1611-3349 ;13810Machine learningCongressesMathematical optimizationCongressesMachine learningMathematical optimization060.68Nicosia GiuseppeMiAaPQMiAaPQMiAaPQBOOK996517755303316Machine learning, optimization, and data science1949690UNISA