A technique for suggesting related Wikipedia articles using link analysis
Document Type
Conference Proceeding
Publication Date
7-11-2012
Abstract
With more than 3.7 million articles, Wikipedia has become an important social medium for sharing knowledge. However, with this enormous repository of information, it can often be difficult to locate fundamental topics that support lower-level articles. By exploiting the information stored in the links between articles, we propose that related companion articles can be automatically generated to help further the reader's understanding of a given topic. This approach to a recommendation system uses tested link analysis techniques to present users with a clear path to related high-level articles, furthering the understanding of low-level topics. © 2012 Authors.
Identifier
84863538698 (Scopus)
ISBN
[9781450311540]
Publication Title
Proceedings of the ACM IEEE Joint Conference on Digital Libraries
External Full Text Location
https://doi.org/10.1145/2232817.2232883
ISSN
15525996
First Page
345
Last Page
346
Recommended Citation
Markson, Christopher and Song, Min, "A technique for suggesting related Wikipedia articles using link analysis" (2012). Faculty Publications. 18172.
https://digitalcommons.njit.edu/fac_pubs/18172
