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- W1969400911 abstract "This paper discusses the problems of analyzing title page layouts and extracting bibliographic informationfrom academic papers. Information extraction is an important task for easily using digital libraries. Sequenceanalyzers are usually used to extract information from pages. Because we often receive new layouts and thelayouts also usually change, it is necessary to have a machenism for self-trainning a new analyzer to achieve agood extraction accuracy. This also makes the management becomes easier. For example, when the new layoutis inputed, There is a problem of how we can learn automatically and efficiently to create a new analyzer. Thispaper focuses on learning a new sequence analyzer automatically by using transfer learning approach. Weevaluated the efficiency by testing three academic journals. The results show that the proposed method iseffective to self-train a new sequence analyer." @default.
- W1969400911 created "2016-06-24" @default.
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- W1969400911 date "2015-01-01" @default.
- W1969400911 modified "2023-09-26" @default.
- W1969400911 title "Transfer Learning for Bibliographic Information Extraction" @default.
- W1969400911 doi "https://doi.org/10.5220/0005283003740379" @default.
- W1969400911 hasPublicationYear "2015" @default.
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