TY - JOUR
T1 - A Specialized Data Crawler for Urban Wood Information
AU - Thomas, R. Edward
AU - Espinoza, Omar
N1 - Publisher Copyright:
ÓForest Products Society 2024.
PY - 2023
Y1 - 2023
N2 - The Internet is composed of .50 billion Web pages and grows larger every day. As the number of links and specialty subject areas increases, it becomes ever more difficult to find pertinent information. For some subject areas, special purpose data crawlers continually search the Internet for specific information; examples include real estate, air travel, auto sales, and others. The use of such special purpose data crawlers (i.e., targeted crawlers and knowledge databases), also allows the collection and analysis of agricultural and forestry data. Such single-purpose crawlers can search for hundreds of keywords and use machine learning to determine whether or not what is found is relevant. In this paper, we examine the design and data return of such a specialty knowledge database and crawler system developed to find information related to urban wood utilization—products made from timber harvested in cities and municipalities. Our search engine uses intelligent software to locate and update pertinent references related to urban wood as well as to categorize information with respect to common application and interest areas. At the time of this publication, the urban wood knowledge database has cataloged .700 publications regarding various aspects of urban wood.
AB - The Internet is composed of .50 billion Web pages and grows larger every day. As the number of links and specialty subject areas increases, it becomes ever more difficult to find pertinent information. For some subject areas, special purpose data crawlers continually search the Internet for specific information; examples include real estate, air travel, auto sales, and others. The use of such special purpose data crawlers (i.e., targeted crawlers and knowledge databases), also allows the collection and analysis of agricultural and forestry data. Such single-purpose crawlers can search for hundreds of keywords and use machine learning to determine whether or not what is found is relevant. In this paper, we examine the design and data return of such a specialty knowledge database and crawler system developed to find information related to urban wood utilization—products made from timber harvested in cities and municipalities. Our search engine uses intelligent software to locate and update pertinent references related to urban wood as well as to categorize information with respect to common application and interest areas. At the time of this publication, the urban wood knowledge database has cataloged .700 publications regarding various aspects of urban wood.
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U2 - 10.13073/FPJ-D-23-00045
DO - 10.13073/FPJ-D-23-00045
M3 - Article
AN - SCOPUS:85186336724
SN - 0015-7473
VL - 73
SP - 350
EP - 356
JO - Forest Products Journal
JF - Forest Products Journal
IS - 4
ER -