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[null,"1.","Record Nr.",null,"UNINA9910467701903321"]
[null,null,"Autore",null,"Kosambi Damodar Dharmanand"]
[null,null,"Titolo",null,"Bhartiya Itihaas Ka Adhyayan Ek Parichay : Ek Parichay"]
[null,null,"Pubbl/distr/stampa",null,"New Delhi : , : SAGE Publications, , 2019"]
[{"$nulls":4},"©2019"]
[null,null,"ISBN",null,"93-5280-590-9"]
[null,null,"Edizione",null,"[2nd ed.]"]
[null,null,"Descrizione fisica",null,"1 online resource (287 pages)"]
[null,null,"Soggetti",null,"Electronic books."]
[null,null,"Lingua di pubblicazione",null,"Hindi"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,"Nota di contenuto",null,"Cover -- Contents -- Preface to the Revised Edition -- Preface to the First Edition -- Publisher's Note -- Abbreviations and Bibliography -- Chronological Outline -- Chapter 1 -- Chapter 2 -- Chapter 3 -- Chapter 4 -- Chapter 5 -- Chapter 6 -- Chapter 7 -- Chapter 8 -- Chapter 9 -- Chapter 10 -- Appendix -- Commentary to the Illustrations."]
[null,"2.","Record Nr.",null,"UNISA996418304203316"]
[null,null,"Titolo",null,"Advanced data mining and applications : 16th international conference, ADMA 2020 Foshan, China, November 12-14, 2020, proceedings / / Xiaochun Yang [and three others] (editors)"]
[null,null,"Pubbl/distr/stampa",null,"Cham, Switzerland : , : Springer, , [2021]"]
[{"$nulls":4},"©2021"]
[null,null,"ISBN",null,"3-030-65390-0"]
[null,null,"Edizione",null,"[1st ed. 2020.]"]
[null,null,"Descrizione fisica",null,"1 online resource (XV, 670 p. 241 illus., 165 illus. in color.)"]
[null,null,"Collana",null,"Lecture Notes in Artificial Intelligence ; ; 12447"]
[null,null,"Disciplina",null,"006.3"]
[null,null,"Soggetti",null,"Data mining"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,"Nota di contenuto",null,"Machine Learning -- Subspace-Weighted Consensus Clustering for High-Dimensional Data -- NOV-RSI: A Novel Optimization Algorithm for Mining Rare Significance Itemsets -- MSPP: A Highly Efficient and Scalable Algorithm for Mining Similar Pairs of Points -- Discovering High Utility Itemsets Using Set-Based Particle Swarm Optimization -- SS-AOE: Subspace based classification framework for avoiding over-confident errors -- Inuence Maximization based Active Learning in Noisy Setting -- Text Mining -- DGRL: Text Classification with Deep Graph Residual Learning -- Densely Connected Bidirectional LSTM With Max-pooling of CNN Network for Text Classification -- A Context-aware Computing Method of Sentence Similarity Based on Frame Semantics -- Learning the Concept Embeddings of Ontology -- ATextCNN Model: A New Multi-Classification Method for Police Situation -- Hierarchical and Pairwise Document Embedding for Plagiarism Detection -- Graph Mining -- Evolutionary strategy for graph embedding -- D2NE: Deep Dynamic Network Embedding -- Elaborating the Bayesian Priors in Unsupervised Graph Embedding via Graph Concepts -- Tuser3: A profile matching based algorithm across three heterogeneous social networks -- Encrypted Traffic Classification using Graph Convolutional Networks -- Representing EHRs with Temporal Tree and Sequential Pattern Mining for Similarity Computing -- Research of Medical Aided Diagnosis System Based on Temporal Knowledge Graph -- TOP-R Keyword-Aware Community Search -- Online Community Identification Over Heterogeneous Attributed Directed Graphs -- Predictive Analytics MPB: Multi-Peak Binarization for "]
[{"$nulls":4},"Pupil Detection -- Rice Leaf Diseases Recognition using Convolutional Neural Networks -- STCNet: Spatial-Temporal Convolution Network for Traffic Speed Prediction -- Discriminative Features Generation for Mortality Prediction in ICU -- Pre-trained StyleGAN based data augmentation for small sample brain CT motion artifacts detection -- Motion Artifacts Detection from Computed Tomography Images -- Loners stand out. Identification of anomalous subsequences based on group performance -- Brain CT Image Augmentation based on PGGAN and FBP for Artifact Detection -- Recursive RNN based Shift Representation Learning for Dynamic User-Item Interaction Prediction -- Computational methods for predicting Autism Spectrum Disorder from gene expression data -- Recommender Systems -- Declarative User-Item Profiling Based Context-Aware Recommendation -- HisRec: Bridging Heterogeneous Information Spaces for Recommendation via Attentive Embedding -- A Neighbor-aware Group Recommendation Algorithm -- Cross Product And Attention Based Deep Neural Collaborative Filtering -- Privacy and Security -- Blockchain-based Privacy Preserving Trust Management Model in VANET -- SecureRec: Privacy-Preserving Recommendation with Distributed Matrix Factorization -- Query Processing -- Optimizing Scoring and Sorting Operations for Faster WAND Processing -- Query-Based Recommendation by HIN Embedding with PRE-LSTM -- Data Mining Applications -- Applications of Big Data in Tourism: A Survey -- High-quality Plane Wave Compounding using Deep Learning for Hand-held Ultrasound Devices -- IPMM: Cancer Subtype Clustering Model Based on Multiomics Data and Pathway and Motif Information -- Personal Health Index based on Residential Health Examination -- Decision support system for acupuncture treatment of ischemic stroke -- Detecting Topic and Sentiment Dynamics Due to COVID-19 Pandemic Using Social Media -- FabricGene: A higher-level feature representation of fabric patterns for nationality classification -- Low-Light Image Enhancement With Color Transfer Based On Local Statistical Feature -- Role-aware Enhanced Matching Network for Multi-Turn Response Selection in Customer Service Chatbots."]
[null,null,null,"Sommario/riassunto","This book constitutes the proceedings of the 16th International Conference on Advanced Data Mining and Applications, ADMA 2020, held in Foshan, China in November 2020. The 35 full papers presented together with 14 short papers papers were carefully reviewed and selected from 96 submissions. The papers were organized in topical sections named: Machine Learning; Text Mining; Graph Mining; Predictive Analytics; Recommender Systems; Privacy and Security; Query Processing; Data Mining Applications."]