Difference between revisions of "Mining Missing Hyperlinks from Human Navigation Traces: a Case Study of Wikipedia"
(Starting an article - Mining Missing Hyperlinks from Human Navigation Traces: a Case Study of Wikipedia) |
(Int.links) |
||
| Line 1: | Line 1: | ||
| − | '''Mining Missing Hyperlinks from Human Navigation Traces: a Case Study of Wikipedia''' - scientific work related to Wikipedia quality published in 2015, written by Robert West, Ashwin Paranjape and Jure Leskovec. | + | '''Mining Missing Hyperlinks from Human Navigation Traces: a Case Study of Wikipedia''' - scientific work related to [[Wikipedia quality]] published in 2015, written by [[Robert West]], [[Ashwin Paranjape]] and [[Jure Leskovec]]. |
== Overview == | == Overview == | ||
| − | Hyperlinks are an essential feature of the World Wide Web. They are especially important for online encyclopedias such as Wikipedia: an article can often only be understood in the context of related articles, and hyperlinks make it easy to explore this context. But important links are often missing, and several methods have been proposed to alleviate this problem by learning a linking model based on the structure of the existing links. Here authors propose a novel approach to identifying missing links in Wikipedia. Authors build on the fact that the ultimate purpose of Wikipedia links is to aid navigation. Rather than merely suggesting new links that are in tune with the structure of existing links, method finds missing links that would immediately enhance Wikipedia's navigability. Authors leverage data sets of navigation paths collected through a Wikipedia-based human-computation game in which users must find a short path from a start to a target article by only clicking links encountered along the way. Authors harness human navigational traces to identify a set of candidates for missing links and then rank these candidates. Experiments show that procedure identifies missing links of high quality. | + | Hyperlinks are an essential feature of the World Wide Web. They are especially important for online encyclopedias such as [[Wikipedia]]: an article can often only be understood in the context of related articles, and hyperlinks make it easy to explore this context. But important links are often missing, and several methods have been proposed to alleviate this problem by learning a linking model based on the structure of the existing links. Here authors propose a novel approach to identifying missing links in Wikipedia. Authors build on the fact that the ultimate purpose of Wikipedia links is to aid navigation. Rather than merely suggesting new links that are in tune with the structure of existing links, method finds missing links that would immediately enhance Wikipedia's navigability. Authors leverage data sets of navigation paths collected through a Wikipedia-based human-computation game in which users must find a short path from a start to a target article by only clicking links encountered along the way. Authors harness human navigational traces to identify a set of candidates for missing links and then rank these candidates. Experiments show that procedure identifies missing links of high quality. |
Revision as of 23:26, 6 July 2019
Mining Missing Hyperlinks from Human Navigation Traces: a Case Study of Wikipedia - scientific work related to Wikipedia quality published in 2015, written by Robert West, Ashwin Paranjape and Jure Leskovec.
Overview
Hyperlinks are an essential feature of the World Wide Web. They are especially important for online encyclopedias such as Wikipedia: an article can often only be understood in the context of related articles, and hyperlinks make it easy to explore this context. But important links are often missing, and several methods have been proposed to alleviate this problem by learning a linking model based on the structure of the existing links. Here authors propose a novel approach to identifying missing links in Wikipedia. Authors build on the fact that the ultimate purpose of Wikipedia links is to aid navigation. Rather than merely suggesting new links that are in tune with the structure of existing links, method finds missing links that would immediately enhance Wikipedia's navigability. Authors leverage data sets of navigation paths collected through a Wikipedia-based human-computation game in which users must find a short path from a start to a target article by only clicking links encountered along the way. Authors harness human navigational traces to identify a set of candidates for missing links and then rank these candidates. Experiments show that procedure identifies missing links of high quality.
