Difference between revisions of "An Exploration of Learning to Link with Wikipedia: Features, Methods and Training Collection"
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| + | {{Infobox work | ||
| + | | title = An Exploration of Learning to Link with Wikipedia: Features, Methods and Training Collection | ||
| + | | date = 2009 | ||
| + | | authors = [[Jiyin He]]<br />[[Maarten De Rijk]] | ||
| + | | doi = 10.1007/978-3-642-14556-8_32 | ||
| + | | link = https://dl.acm.org/citation.cfm?id=1881065.1881104 | ||
| + | }} | ||
'''An Exploration of Learning to Link with Wikipedia: Features, Methods and Training Collection''' - scientific work related to [[Wikipedia quality]] published in 2009, written by [[Jiyin He]] and [[Maarten De Rijk]]. | '''An Exploration of Learning to Link with Wikipedia: Features, Methods and Training Collection''' - scientific work related to [[Wikipedia quality]] published in 2009, written by [[Jiyin He]] and [[Maarten De Rijk]]. | ||
== Overview == | == Overview == | ||
Authors describe participation in the Link-the-Wiki track at INEX 2009. Authors apply machine learning methods to the anchor-to-best-entry-point task and explore the impact of the following aspects of approaches: [[features]], learning methods as well as the collection used for training the models. Authors find that a learning to rank-based approach and a binary classification approach do not differ a lot. The new [[Wikipedia]] collection which is of larger size and which has more links than the collection previously used, provides better training material for learning models. In addition, a heuristic run which combines the two intuitively most useful features outperforms machine learning based runs, which suggests that a further analysis and selection of features is necessary. | Authors describe participation in the Link-the-Wiki track at INEX 2009. Authors apply machine learning methods to the anchor-to-best-entry-point task and explore the impact of the following aspects of approaches: [[features]], learning methods as well as the collection used for training the models. Authors find that a learning to rank-based approach and a binary classification approach do not differ a lot. The new [[Wikipedia]] collection which is of larger size and which has more links than the collection previously used, provides better training material for learning models. In addition, a heuristic run which combines the two intuitively most useful features outperforms machine learning based runs, which suggests that a further analysis and selection of features is necessary. | ||
Revision as of 09:56, 2 August 2019
Authors | Jiyin He Maarten De Rijk |
|---|---|
Publication date | 2009 |
DOI | 10.1007/978-3-642-14556-8_32 |
Links | Original |
An Exploration of Learning to Link with Wikipedia: Features, Methods and Training Collection - scientific work related to Wikipedia quality published in 2009, written by Jiyin He and Maarten De Rijk.
Overview
Authors describe participation in the Link-the-Wiki track at INEX 2009. Authors apply machine learning methods to the anchor-to-best-entry-point task and explore the impact of the following aspects of approaches: features, learning methods as well as the collection used for training the models. Authors find that a learning to rank-based approach and a binary classification approach do not differ a lot. The new Wikipedia collection which is of larger size and which has more links than the collection previously used, provides better training material for learning models. In addition, a heuristic run which combines the two intuitively most useful features outperforms machine learning based runs, which suggests that a further analysis and selection of features is necessary.
