LEADER 03405nam 2200541Ia 450 001 9910437560803321 005 20200520144314.0 010 $a1-299-19712-4 010 $a1-4471-4890-8 024 7 $a10.1007/978-1-4471-4890-6 035 $a(OCoLC)826858923 035 $a(MiFhGG)GVRL6XXB 035 $a(CKB)2560000000100045 035 $a(MiAaPQ)EBC1081798 035 $a(EXLCZ)992560000000100045 100 $a20130206d2013 uy 0 101 0 $aeng 135 $aurun|---uuuua 181 $ctxt 182 $cc 183 $acr 200 10$aData mining in large sets of complex data /$fRobson L. F. Cordeiro, Christos Faloutsos, Caetano Traina Junior 205 $a1st ed. 2013. 210 $aLondon ;$aNew York $cSpringer$dc2013 215 $a1 online resource (xi, 116 pages) $cillustrations (some color) 225 0$aSpringerBriefs in computer science,$x2191-5768 300 $a"ISSN: 2191-5768." 311 $a1-4471-4889-4 320 $aIncludes bibliographical references. 327 $aPreface -- Introduction -- Related Work and Concepts -- Clustering Methods for Moderate-to-High Dimensionality Data -- Halite -- BoW -- QMAS -- Conclusion. 330 $aThe amount and the complexity of the data gathered by current enterprises are increasing at an exponential rate. Consequently, the analysis of Big Data is nowadays a central challenge in Computer Science, especially for complex data. For example, given a satellite image database containing tens of Terabytes, how can we find regions aiming at identifying native rainforests, deforestation or reforestation? Can it be made automatically? Based on the work discussed in this book, the answers to both questions are a sound ?yes?, and the results can be obtained in just minutes. In fact, results that used to require days or weeks of hard work from human specialists can now be obtained in minutes with high precision. Data Mining in Large Sets of Complex Data discusses new algorithms that take steps forward from traditional data mining (especially for clustering) by considering large, complex datasets. Usually, other works focus in one aspect, either data size or complexity. This work considers both: it enables mining complex data from high impact applications, such as breast cancer diagnosis, region classification in satellite images, assistance to climate change forecast, recommendation systems for the Web and social networks; the data are large in the Terabyte-scale, not in Giga as usual; and very accurate results are found in just minutes. Thus, it provides a crucial and well timed contribution for allowing the creation of real time applications that deal with Big Data of high complexity in which mining on the fly can make an immeasurable difference, such as supporting cancer diagnosis or detecting deforestation. 410 0$aSpringerBriefs in computer science. 606 $aData mining 606 $aDatabase searching 615 0$aData mining. 615 0$aDatabase searching. 676 $a006.312 686 $aST 530$2rvk 700 $aCordeiro$b Robson L. F$01751801 701 $aFaloutsos$b Christos$0746292 701 $aTraina Junior$b Caetano$01751802 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910437560803321 996 $aData mining in large sets of complex data$94186914 997 $aUNINA