LEADER 05368nam 22006375 450 001 996466443103316 005 20200706152349.0 010 $a3-030-29249-5 024 7 $a10.1007/978-3-030-29249-2 035 $a(CKB)4100000009160273 035 $a(DE-He213)978-3-030-29249-2 035 $a(MiAaPQ)EBC5921627 035 $a(PPN)243768516 035 $a(EXLCZ)994100000009160273 100 $a20190808d2019 u| 0 101 0 $aeng 135 $aurnn|008mamaa 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aCase-Based Reasoning Research and Development$b[electronic resource] $e27th International Conference, ICCBR 2019, Otzenhausen, Germany, September 8?12, 2019, Proceedings /$fedited by Kerstin Bach, Cindy Marling 205 $a1st ed. 2019. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2019. 215 $a1 online resource (XXI, 405 p. 158 illus., 88 illus. in color.) 225 1 $aLecture Notes in Artificial Intelligence ;$v11680 300 $aIncludes index. 311 $a3-030-29248-7 327 $aComparing Similarity Learning with Taxonomies and One-Mode Projection in Context of the FEATURE-TAK Framework -- An Algorithm Independent Case-Based Explanation Approach for Recommender Systems Using Interaction Graphs -- Explanation of Recommender Systems using Formal Concept Analysis -- FLEA-CBR { A Flexible Alternative to the Classic 4R Cycle of Lazy Learned Screening for Efficient Recruitment -- Case-Based Reasoning -- On the Generalization Capabilities of Sharp Minima in Case-Based Reasoning -- CBR Confidence as a Basis for Confidence in Black Box Systems -- Probabilistic Selection of Case-Based Explanations in an Underwater Mine Clearance Domain -- A Data-Driven Approach for Determining Weights in Global Similarity Functions -- Personalized case-based explanation of matrix factorization Recommendations -- How Case-Based Reasoning Explains Neural Networks -- Predicting Grass Growth for Sustainable Dairy Farming: A CBR System Using Bayesian Case-Exclusion and Post-Hoc, Personalized Explanation-by-Example (XAI) -- Learning Workflow Embeddings to Improve the Performance of Similarity-Based Retrieval for Process-Oriented Case-Based Reasoning -- On Combining Case Adaptation Rules -- Semantic Textual Similarity Measures for Case-Based Retrieval of Argument Graphs -- An approach to case-based reasoning based on local enrichment of the case base -- Improving analogical extrapolation using case pair competence -- Towards Finding Flow in Tetris -- Scoring Performance on the Y-Balance Test -- An Optimal Case-base Maintenance Method for Compositional Adaptation Applications -- Towards Human-like Bots using Online Interactive Case-Based Reasoning -- Show me your friends, I'll tell you who you are: Recommending products based on hidden evidence -- A Tale of Two Communities: An Analysis of Three Decades of Case-Based Reasoning Research -- Going Further with Cases: Using Case-Based Reasoning to Recommend Pacing Strategies for Ultra-Marathon Runners -- NOD-CC: A Hybrid CBR-CNN Architecture for Novel Object Discovery -- Adaptation of Scientific Workflows by Means of Process-Oriented Case-Based Reasoning. 330 $aThis book constitutes the refereed proceedings of the 27th International Conference on Case-Based Reasoning Research and Development, ICCBR 2019, held in Otzenhausen, Germany, in September 2019. The 26 full papers presented in this book were carefully reviewed and selected from 43 submissions. 15 were selected for oral presentation and 11 for poster presentation. The theme of ICCBR 2019, "Explainable AI (XAI)," was highlighted by several activities. These papers, which are included in the proceedings, address many themes related to the theory and application of case-based reasoning and its future direction. 410 0$aLecture Notes in Artificial Intelligence ;$v11680 606 $aArtificial intelligence 606 $aApplication software 606 $aInformation storage and retrieval 606 $aData mining 606 $aArtificial Intelligence$3https://scigraph.springernature.com/ontologies/product-market-codes/I21000 606 $aComputer Appl. in Administrative Data Processing$3https://scigraph.springernature.com/ontologies/product-market-codes/I2301X 606 $aInformation Storage and Retrieval$3https://scigraph.springernature.com/ontologies/product-market-codes/I18032 606 $aData Mining and Knowledge Discovery$3https://scigraph.springernature.com/ontologies/product-market-codes/I18030 615 0$aArtificial intelligence. 615 0$aApplication software. 615 0$aInformation storage and retrieval. 615 0$aData mining. 615 14$aArtificial Intelligence. 615 24$aComputer Appl. in Administrative Data Processing. 615 24$aInformation Storage and Retrieval. 615 24$aData Mining and Knowledge Discovery. 676 $a153.43 702 $aBach$b Kerstin$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aMarling$b Cindy$4edt$4http://id.loc.gov/vocabulary/relators/edt 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a996466443103316 996 $aCase-Based Reasoning Research and Development$9771966 997 $aUNISA