%0 Journal Article %1 Day07 %A Day, Min-Yuh %A Tsai, Richard Tzong-Han %A Sung, Cheng-Lung %A Hsieh, Chiu-Chen %A Lee, Cheng-Wei %A Wu, Shih-Hung %A Wu, Kun-Pin %A Ong, Chorng-Shyong %A Hsu, Wen-Lian %D 2007 %J Decision Support Systems %K extraktion referenzen %N 1 %P 152-167 %R DOI: 10.1016/j.dss.2006.08.006 %T Reference metadata extraction using a hierarchical knowledge representation framework %U http://www.sciencedirect.com/science/article/B6V8S-4M0J49C-1/2/7350cc23dee69fab71c13d64bc28e633 %V 43 %X The integration of bibliographical information on scholarly publications available on the Internet is an important task in the academic community. Accurate reference metadata extraction from such publications is essential for the integration of metadata from heterogeneous reference sources. In this paper, we propose a hierarchical template-based reference metadata extraction method for scholarly publications. We adopt a hierarchical knowledge representation framework called INFOMAP, which automatically extracts metadata. The experimental results show that, by using INFOMAP, we can extract author, title, journal, volume, number (issue), year, and page information from different kinds of reference styles with a high degree of precision. The overall average accuracy is 92.39% for the six major reference styles compared in this study.

@article{Day07, abstract = {The integration of bibliographical information on scholarly publications available on the Internet is an important task in the academic community. Accurate reference metadata extraction from such publications is essential for the integration of metadata from heterogeneous reference sources. In this paper, we propose a hierarchical template-based reference metadata extraction method for scholarly publications. We adopt a hierarchical knowledge representation framework called INFOMAP, which automatically extracts metadata. The experimental results show that, by using INFOMAP, we can extract author, title, journal, volume, number (issue), year, and page information from different kinds of reference styles with a high degree of precision. The overall average accuracy is 92.39% for the six major reference styles compared in this study.}, added-at = {2009-09-30T16:50:31.000+0200}, author = {Day, Min-Yuh and Tsai, Richard Tzong-Han and Sung, Cheng-Lung and Hsieh, Chiu-Chen and Lee, Cheng-Wei and Wu, Shih-Hung and Wu, Kun-Pin and Ong, Chorng-Shyong and Hsu, Wen-Lian}, biburl = {https://www.bibsonomy.org/bibtex/24408ef8a3ad25c10d3c8019fbcc49a16/wdees}, doi = {DOI: 10.1016/j.dss.2006.08.006}, interhash = {501f67ec55ccc5abcfdb69a126b4e55a}, intrahash = {4408ef8a3ad25c10d3c8019fbcc49a16}, issn = {0167-9236}, journal = {Decision Support Systems}, keywords = {extraktion referenzen}, note = {Mobile Commerce: Strategies, Technologies, and Applications}, number = 1, pages = {152-167}, timestamp = {2009-09-30T16:50:31.000+0200}, title = {Reference metadata extraction using a hierarchical knowledge representation framework}, url = {http://www.sciencedirect.com/science/article/B6V8S-4M0J49C-1/2/7350cc23dee69fab71c13d64bc28e633}, volume = 43, year = 2007 }