LEADER 01571nam2-2200421---450- 001 990000331210203316 035 $a0033121 035 $aUSA010033121 035 $a(ALEPH)000033121USA01 035 $a0033121 100 $a20010131d1998----km-y0itay0103----ba 101 0 $aita 102 $aIT 105 $a||||||||001yy 200 1 $a<> metallurgia e i mezzi di trasporto costruzione e riparazione$einfortuni sul lavoro$e1998$fIstituto Nazionale per l'Assicurazione contro gli Infortuni sul lavoro$v2 210 $aRoma$cInail$d1998 215 $a83 p.$c42 c. di tav.$d30 cm 225 2 $aQuaderni del Notiziario Statistico dell'Inail 300 $aSuppl. a: Notiziario Statistico n.4, 1998 410 0$12001 461 0 $10010033118$12001$aStatistiche per la prevenzione 606 $aInfortuni sul lavoro$xPrevenzione$yItalia 606 $aAgricoltura e industria$xInfortuni sul lavoro$xStatistica$z1998 676 $a363.110945 712 02$aIstituto Nazionale per l'Assicurazione contro gli Infortuni sul lavoro 801 0$aIT$bsalbc$gISBD 912 $a990000331210203316 951 $aCOLL. HAI 28/2$b26554 G.$cCOLL. HAI$d00006104 959 $aBK 969 $aGIU 979 $aTAMI$b40$c20010131$lUSA01$h1107 979 $aTAMI$b40$c20010131$lUSA01$h1108 979 $aTAMI$b40$c20010201$lUSA01$h0858 979 $aTAMI$b40$c20010201$lUSA01$h1026 979 $c20020403$lUSA01$h1641 979 $aPATRY$b90$c20040406$lUSA01$h1623 996 $aMetallurgia e i mezzi di trasporto costruzione e riparazione$9879548 997 $aUNISA LEADER 05595nam 22006615 450 001 9910364954403321 005 20200630124043.0 010 $a3-030-37188-3 024 7 $a10.1007/978-3-030-37188-3 035 $a(CKB)4100000010013766 035 $a(MiAaPQ)EBC5997053 035 $a(DE-He213)978-3-030-37188-3 035 $a(PPN)242818560 035 $a(EXLCZ)994100000010013766 100 $a20191212d2019 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aBig Data Analytics $e7th International Conference, BDA 2019, Ahmedabad, India, December 17?20, 2019, Proceedings /$fedited by Sanjay Madria, Philippe Fournier-Viger, Sanjay Chaudhary, P. Krishna Reddy 205 $a1st ed. 2019. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2019. 215 $a1 online resource (466 pages) 225 1 $aInformation Systems and Applications, incl. Internet/Web, and HCI ;$v11932 311 $a3-030-37187-5 327 $aBig Data Analytics: Vision and Perspectives -- Transforming Sensing Data into Smart Data for Smart Sustainable Cities -- Deep Learning Models for Medical Image Analysis: Challenges and Future Directions -- Recent Advances and Challenges in design of Non-Goal Oriented Dialogue System -- Data Cube is Dead, Long Life to Data Cube in the Age of Web Data -- Search and Information Extraction -- Improving Result Diversity using Query Term Proximity in Exploratory Search -- Segment-search vs Knowledge Graphs: Making a Keyword Search Engine for Web Documents -- Pairing Users in Social Media via Processing Meta-data from Conversational Files -- Large-Scale Information Extraction from Emails with Data Constraints -- Comparative Analysis of Rule-based, Dictionary-based and Hybrid Stemmers for Gujarati Language -- Predictive Analytics in Medical and Agricultural Domains -- Artificial Intelligence and Bayesian Knowledge Network in Health Care ? Smartphone Apps for diagnosis and differentiation of anemias with higher accuracy at Resource Constrained Point-of-Care settings -- Analyzing Domain Knowledge for Big Data Analysis: A Case Study with Urban Tree Type Classification -- Market Intelligence for Agricultural Commodities using Forecasting and Deep Learning Techniques -- Graph Analytics -- TKG: Efficient Mining of Top-K Frequent Subgraphs -- Why Multilayer Networks Instead Of Simple Graphs? Modeling Effectiveness And Analysis Flexibility & Efficiency! -- Gossip Based Distributed Real Time Task Scheduling with Guaranteed Performance on Heterogeneous Networks -- Data-Driven Optimization of Public Transit Schedule -- Pattern Mining -- Discovering Spatial High Utility Frequent Itemsets in Spatiotemporal Databases -- Efficient Algorithms For Flock Detection in Large Spatio-Temporal Data -- Local Temporal Compression for (Globally) Evolving Spatial Surfaces -- An Explicit Relationship between Sequential Patterns and their Concise Representations -- Machine Learning -- A novel approach to identify the determinants of online review helpfulness and predict the helpfulness score across product categories -- Analysis and Recognition of Hand-drawn Images with Effective Data Handling -- Real Time Static Gesture Detection Using Deep Learning -- Interpreting Context of Images using Scene Graphs -- Deep Learning in the Domain of Near-Duplicate Document Detection. 330 $aThis book constitutes the refereed proceedings of the 7th International Conference on Big Data analytics, BDA 2019, held in Ahmedabad, India, in December 2019. The 25 papers presented in this volume were carefully reviewed and selected from 53 submissions. The papers are organized in topical sections named: big data analytics: vision and perspectives; search and information extraction; predictive analytics in medical and agricultural domains; graph analytics; pattern mining; and machine learning. 410 0$aInformation Systems and Applications, incl. Internet/Web, and HCI ;$v11932 606 $aData mining 606 $aArtificial intelligence 606 $aApplication software 606 $aDatabase management 606 $aData Mining and Knowledge Discovery$3https://scigraph.springernature.com/ontologies/product-market-codes/I18030 606 $aArtificial Intelligence$3https://scigraph.springernature.com/ontologies/product-market-codes/I21000 606 $aInformation Systems Applications (incl. Internet)$3https://scigraph.springernature.com/ontologies/product-market-codes/I18040 606 $aDatabase Management$3https://scigraph.springernature.com/ontologies/product-market-codes/I18024 615 0$aData mining. 615 0$aArtificial intelligence. 615 0$aApplication software. 615 0$aDatabase management. 615 14$aData Mining and Knowledge Discovery. 615 24$aArtificial Intelligence. 615 24$aInformation Systems Applications (incl. Internet). 615 24$aDatabase Management. 676 $a005.7 676 $a006.312 702 $aMadria$b Sanjay$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aFournier-Viger$b Philippe$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aChaudhary$b Sanjay$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aReddy$b P. Krishna$4edt$4http://id.loc.gov/vocabulary/relators/edt 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910364954403321 996 $aBig data analytics$91523196 997 $aUNINA