000 06322cam a2200769 i 4500
001 on1268983409
003 OCoLC
005 20250707094101.0
006 m o d
007 cr |n|||||||||
008 210923s2021 sz a o 101 0 eng d
040 _aYDX
_beng
_erda
_epn
_cYDX
_dGW5XE
_dOCLCO
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_dOCLCF
_dOCLCO
_dOCLCQ
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020 _a9783030855291
_q(electronic bk.)
020 _a3030855295
_q(electronic bk.)
020 _z9783030855284
020 _z3030855287
024 7 _a10.1007/978-3-030-85529-1
_2doi
029 1 _aAU@
_b000069954815
029 1 _aAU@
_b000070137060
035 _a(OCoLC)1268983409
050 4 _aQ334.M43
_bM43 2021
072 7 _aUYQ
_2bicssc
072 7 _aCOM004000
_2bisacsh
072 7 _aUYQ
_2thema
082 0 4 _a006.3
_223
049 _aMAIN
111 2 _aMDAI (Conference)
_n(18th :
_d2021 :
_cOnline)
245 1 0 _aModeling decisions for artificial intelligence :
_b18th international conference, MDAI 2021, Umeå, Sweden, September 27-30, 2021 : proceedings /
_cVicenç Torra, Yasuo Narukawa (eds.).
246 3 0 _aMDAI 2021
264 1 _aCham :
_bSpringer,
_c[2021]
264 4 _c©2021
300 _a1 online resource :
_billustrations (some color)
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
490 1 _aLecture notes in computer science. Lecture notes in artificial intelligence ;
_v12898
490 1 _aLNCS sublibrary: SL7 - Artificial intelligence
500 _aInternational conference proceedings.
500 _aIncludes author index.
520 _aThis book constitutes the refereed proceedings of the 18th International Conference on Modeling Decisions for Artificial Intelligence, MDAI 2021, held in Umeå, Sweden, in September 2021.* The 24 papers presented in this volume were carefully reviewed and selected from 50 submissions. Additionally, 3 invited papers were included. The papers discuss different facets of decision processes in a broad sense and present research in data science, data privacy, aggregation functions, human decision making, graphs and social networks, and recommendation and search. The papers are organized in the following topical sections: aggregation operators and decision making; approximate reasoning; machine learning; data science and data privacy. *The conference was held virtually due to the COVID-19 pandemic.
505 0 _aInvited Papers -- Andness-Directed Iterative OWA Aggregators -- New Eliahou semigroups and verification of the Wilf conjecture for genus up to 65 -- Are Sequential Patterns Shareable? Ensuring Individuals' Privacy -- Aggregation Operators and Decision Making -- On Two Generalizations for k-additivity -- Sequential decision-making using hybrid probability-possibility functions -- Numerical comparison of idempotent andness-directed aggregators -- Approximate Reasoning -- Multiple testing of conditional independence hypotheses using information-theoretic approach -- A Bayesian Interpretation of the Monty Hall Problem with Epistemic Uncertainty -- How the F-transform can be defined for hesitant, soft or intuitionistic fuzzy sets? Enhancing social recommenders with implicit preferences and fuzzy confidence functions -- A Necessity Measure of Fuzzy Inclusion Relation in Linear Programming Problems -- Machine Learning -- Mass-based Similarity Weighted k-Neighbor for Class Imbalance -- Multinomial-based Decision Synthesis of ML Classification Outputs -- Quantile Encoder: Tackling High Cardinality Categorical Features in Regression Problems -- Evidential undersampling approach for imbalanced datasets with class-overlapping and noise -- Well-Calibrated and Sharp Interpretable Multi-Class Models -- Automated Attribute Weighting Fuzzy k-Centers Algorithm for Categorical Data Clustering -- q-Divergence Regularization of Bezdek-Type Fuzzy Clustering for Categorical Multivariate Data -- Automatic Clustering of CT Scans of COVID-19 Patients Based on Deep Learning -- Network Clustering with Controlled Node Size -- Data Science and Data Privacy -- Fair-ly Private Through Group Tagging and Relation Impact -- MEDICI: A simple to use synthetic social network data generator -- Answer Passage Ranking Enhancement Using Shallow Linguistic Features -- Neural embedded Dirichlet Processes for topic modeling -- Density-Based Evaluation Metrics in Unsupervised Anomaly Detection Contexts -- Explaining Image Misclassification in Deep Learning via Adversarial Examples.-Towards Machine Learning-Assisted Output Checking for Statistical Disclosure Control --
588 0 _aOnline resource; title from PDF title page (SpringerLink, viewed September 24, 2021).
650 0 _aArtificial intelligence
_xMathematical models
_vCongresses.
_919314
650 0 _aDecision making
_xMathematical models
_vCongresses.
_922338
650 0 _aComputer simulation
_vCongresses.
650 6 _aIntelligence artificielle
_xModèles mathématiques
_vCongrès.
_920037
650 6 _aPrise de décision
_xModèles mathématiques
_vCongrès.
_920038
650 6 _aSimulation par ordinateur
_vCongrès.
_918853
650 7 _aArtificial intelligence
_xMathematical models
_2fast
_919318
650 7 _aComputer simulation
_2fast
_92625
650 7 _aDecision making
_xMathematical models
_2fast
_922340
655 2 _aCongress
_911670
655 7 _aproceedings (reports)
_2aat
655 7 _aConference papers and proceedings
_2fast
_96065
655 7 _aConference papers and proceedings.
_2lcgft
_96065
655 7 _aActes de congrès.
_2rvmgf
_9609890
700 1 _aTorra, Vicenç,
_eeditor.
_920045
700 1 _aNarukawa, Yasuo,
_eeditor.
_920046
776 0 8 _iPrint version:
_aMDAI (Conference) (18th : 2021 : Online).
_tModeling decisions for artificial intelligence.
_dCham : Springer, [2021]
_z3030855287
_z9783030855284
_w(OCoLC)1261362409
830 0 _aLecture notes in computer science ;
_v12898.
830 0 _aLecture notes in computer science.
_pLecture notes in artificial intelligence.
_914916
830 0 _aLNCS sublibrary.
_nSL 7,
_pArtificial intelligence.
_920712
856 4 0 _uhttps://link.springer.com/10.1007/978-3-030-85529-1
938 _aProQuest Ebook Central
_bEBLB
_nEBL6730136
938 _aYBP Library Services
_bYANK
_n302468397
994 _a92
_bATIST
999 _c648922
_d648922