Agricultural Information Research
Online ISSN : 1881-5219
Print ISSN : 0916-9482
ISSN-L : 0916-9482
Volume 19, Issue 1
Displaying 1-2 of 2 articles from this issue
Original Articles
  • Yukio Magariyama, Kumiko Shichiri, Akihiro Miyanoshita, Taro Imamura
    2010 Volume 19 Issue 1 Pages 1-9
    Published: 2010
    Released on J-STAGE: April 01, 2010
    JOURNAL FREE ACCESS
    We performed an access analysis of an illustrated guide on the Internet about insect pests of food and their natural enemies made available to the public by the National Food Research Institute. The numbers of visits to most pest pages showed regular seasonal changes that resembled the changes in pest numbers. In addition, increases corresponding to occasional increases in pest activity sometimes appeared. These results suggest that the number of visits reflects the public awareness of an insect pest. Referrer analysis suggested that the 53 species of insects in the guide should be classified into two groups according to public attention.
    Download PDF (733K)
  • Akane Takezaki, Takashi Hosobami, Daisuke Horyu, Takuji Kiura
    2010 Volume 19 Issue 1 Pages 10-15
    Published: 2010
    Released on J-STAGE: April 01, 2010
    JOURNAL FREE ACCESS
    We compiled rich linguistic resources (such as a morpheme dictionary and a stop list) for automatic indexing of agricultural literature. Terms from agricultural dictionaries, registered plant variety names, and new terms extracted from records in the Japan Agricultural Science Index (JASI) were incorporated into an agricultural morpheme dictionary. The addition of new terms identified by morpheme analysis of JASI records decreased the number of unknown words in subsequent analyses. Combining general and enriched agricultural morpheme dictionaries left fewer unknown words extracted by morpheme analysis than using the general morpheme dictionary only. One-roman letters with the exception of atomic symbols, SI units, reference terms, Indo-Arabic numerals, and numerals were chosen as stop words. Two-thirds of manually indexed terms corresponded completely or partially to automatically indexed terms when both the enriched morpheme dictionary and stop list were used. These results suggest that compiled linguistic resources can improve morpheme analysis and automatic indexing.
    Download PDF (519K)
feedback
Top