Forestry big data platform by Knowledge Graph
Using the advantages of web crawlers in data collection and distributed storage technologies, we accessed to a wealth of forestry-related data. Combined with the mature big data technology at its present stage, Hadoop’s distributed system was selected to solve the storage problem of massive forestry...
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Published in | Journal of forestry research Vol. 32; no. 3; pp. 1305 - 1314 |
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Main Authors | , , |
Format | Journal Article |
Language | English |
Published |
Berlin/Heidelberg
Springer Berlin Heidelberg
01.06.2021
Springer Springer Nature B.V Northeast Forestry University , Harbin 150040 , People's Republic of China |
Subjects | |
Online Access | Get full text |
ISSN | 1007-662X 1993-0607 |
DOI | 10.1007/s11676-020-01130-w |
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Abstract | Using the advantages of web crawlers in data collection and distributed storage technologies, we accessed to a wealth of forestry-related data. Combined with the mature big data technology at its present stage, Hadoop’s distributed system was selected to solve the storage problem of massive forestry big data and the memory-based Spark computing framework to realize real-time and fast processing of data. The forestry data contains a wealth of information, and mining this information is of great significance for guiding the development of forestry. We conducts co-word and cluster analyses on the keywords of forestry data, extracts the rules hidden in the data, analyzes the research hotspots more accurately, grasps the evolution trend of subject topics, and plays an important role in promoting the research and development of subject areas. The co-word analysis and clustering algorithm have important practical significance for the topic structure, research hotspot or development trend in the field of forestry research. Distributed storage framework and parallel computing have greatly improved the performance of data mining algorithms. Therefore, the forestry big data mining system by big data technology has important practical significance for promoting the development of intelligent forestry. |
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AbstractList | Using the advantages of web crawlers in data collection and distributed storage technologies, we accessed to a wealth of forestry-related data. Combined with the mature big data technology at its present stage, Hadoop’s distributed system was selected to solve the storage problem of massive forestry big data and the memory-based Spark computing framework to realize real-time and fast processing of data. The forestry data contains a wealth of information, and mining this information is of great significance for guiding the development of forestry. We conducts co-word and cluster analyses on the keywords of forestry data, extracts the rules hidden in the data, analyzes the research hotspots more accurately, grasps the evolution trend of subject topics, and plays an important role in promoting the research and development of subject areas. The co-word analysis and clustering algorithm have important practical significance for the topic structure, research hotspot or development trend in the field of forestry research. Distributed storage framework and parallel computing have greatly improved the performance of data mining algorithms. Therefore, the forestry big data mining system by big data technology has important practical significance for promoting the development of intelligent forestry. Using the advantages of web crawlers in data col-lection and distributed storage technologies, we accessed to a wealth of forestry-related data. Combined with the mature big data technology at its present stage, Hadoop's distributed system was selected to solve the storage problem of massive forestry big data and the memory-based Spark computing framework to realize real-time and fast processing of data. The forestry data contains a wealth of information, and min-ing this information is of great significance for guiding the development of forestry. We conducts co-word and cluster analyses on the keywords of forestry data, extracts the rules hidden in the data, analyzes the research hotspots more accu-rately, grasps the evolution trend of subject topics, and plays an important role in promoting the research and develop-ment of subject areas. The co-word analysis and clustering algorithm have important practical significance for the topic structure, research hotspot or development trend in the field of forestry research. Distributed storage framework and par-allel computing have greatly improved the performance of data mining algorithms. Therefore, the forestry big data min-ing system by big data technology has important practical significance for promoting the development of intelligent forestry. |
Audience | Academic |
Author | Zhao, Mengxi Long, Yongshen Li, Dan |
AuthorAffiliation | Northeast Forestry University , Harbin 150040 , People's Republic of China |
AuthorAffiliation_xml | – name: Northeast Forestry University , Harbin 150040 , People's Republic of China |
Author_xml | – sequence: 1 givenname: Mengxi surname: Zhao fullname: Zhao, Mengxi organization: Northeast Forestry University – sequence: 2 givenname: Dan surname: Li fullname: Li, Dan email: 2393901357@qq.com organization: Northeast Forestry University – sequence: 3 givenname: Yongshen surname: Long fullname: Long, Yongshen organization: Northeast Forestry University |
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Cites_doi | 10.1007/BF02019280 10.3233/SW-160218 10.14778/2732951.2732962 10.1007/s00420-008-0376-3 10.1016/j.jclepro.2016.02.078 10.1111/j.1541-0072.1995.tb01740.x 10.1505/146554814813484112 10.1080/13504500902794000 10.1007/s11192-011-0586-4 10.1016/j.eswa.2012.01.210 10.3758/s13414-015-0858-9 10.3390/f6030533 10.1109/FSKD.2015.7382112 10.1109/WI-IAT.2011.253 10.1109/CTS.2014.6867550 10.1145/2623330.2623623 10.2514/6.2006-1683 10.1109/ICDMW.2012.115 |
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Copyright | Northeast Forestry University 2020 COPYRIGHT 2021 Springer Northeast Forestry University 2020. Copyright © Wanfang Data Co. Ltd. All Rights Reserved. |
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GrantInformation_xml | – fundername: We acknowledge grants from the Fundamental (Research Funds for the Central Universities); and Special Funds for Scientific Research in the (Forestry Public Welfare Industry) funderid: We acknowledge grants from the Fundamental (Research Funds for the Central Universities); and Special Funds for Scientific Research in the (Forestry Public Welfare Industry) |
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Snippet | Using the advantages of web crawlers in data collection and distributed storage technologies, we accessed to a wealth of forestry-related data. Combined with... Using the advantages of web crawlers in data col-lection and distributed storage technologies, we accessed to a wealth of forestry-related data. Combined with... |
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SubjectTerms | Algorithms Big Data Biomedical and Life Sciences Clustering Computer networks Data collection Data mining evolution Forest management Forestry Forestry research Forests and forestry Geospatial data Information storage and retrieval Knowledge representation Life Sciences Original Paper R&D Research & development research and development |
Title | Forestry big data platform by Knowledge Graph |
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