caa a22 4500 445871229 CHVBK 20180317145512.0 cr unu---uuuuu 170323e20110701xx s 000 0 eng 10.1007/s10618-010-0200-z doi (NATIONALLICENCE)springer-10.1007/s10618-010-0200-z An efficient and effective similarity measure to enable data mining of petroglyphs [Elektronische Daten] [Qiang Zhu, Xiaoyue Wang, Eamonn Keogh, Sang-Hee Lee] Rock art is an archaeological term for human-made markings on stone, including carved markings, known as petroglyphs, and painted markings, known as pictographs. It is believed that there are millions of petroglyphs in North America alone, and the study of this valued cultural resource has implications even beyond anthropology and history. Surprisingly, although image processing, information retrieval and data mining have had a large impact on many human endeavors, they have had essentially zero impact on the study of rock art. In this work we identify the reasons for this, and introduce a novel distance measure and algorithms which allow efficient and effective data mining of large collections of rock art. The Author(s), 2010 Image processing nationallicence Similarity search nationallicence Cultural artifacts nationallicence Zhu Qiang Department of Computer Science and Engineering, University of California Riverside, 92521, Riverside, CA, USA aut Wang Xiaoyue Department of Computer Science and Engineering, University of California Riverside, 92521, Riverside, CA, USA aut Keogh Eamonn Department of Computer Science and Engineering, University of California Riverside, 92521, Riverside, CA, USA aut Lee Sang-Hee Department of Anthropology, University of California Riverside, 92521, Riverside, CA, USA aut Data Mining and Knowledge Discovery Springer US; http://www.springer-ny.com 23/1(2011-07-01), 91-127 1384-5810 23:1<91 2011 23 10618 https://doi.org/10.1007/s10618-010-0200-z text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1007/s10618-010-0200-z text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Zhu Qiang Department of Computer Science and Engineering, University of California Riverside, 92521, Riverside, CA, USA aut NATIONALLICENCE 700 1- Wang Xiaoyue Department of Computer Science and Engineering, University of California Riverside, 92521, Riverside, CA, USA aut NATIONALLICENCE 700 1- Keogh Eamonn Department of Computer Science and Engineering, University of California Riverside, 92521, Riverside, CA, USA aut NATIONALLICENCE 700 1- Lee Sang-Hee Department of Anthropology, University of California Riverside, 92521, Riverside, CA, USA aut NATIONALLICENCE 773 0- Data Mining and Knowledge Discovery Springer US; http://www.springer-ny.com 23/1(2011-07-01), 91-127 1384-5810 23:1<91 2011 23 10618 Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer