# Recognizing Descriptive Wikipedia Categories for Historical Figures

**Authors:** Yanqing Chen, Steven Skiena

arXiv: 1704.07427 · 2017-04-26

## TL;DR

This paper proposes a method to identify the most descriptive Wikipedia categories for historical figures by evaluating their coherence based on texts and links, achieving high agreement with human judgment.

## Contribution

It introduces a novel approach to rank Wikipedia categories by their descriptive power using coherence measures among category members.

## Key findings

- Achieved 88.27% agreement with human judgments
- Effectively identifies the most descriptive categories for historical figures
- Enhances understanding of category relevance in Wikipedia

## Abstract

Wikipedia is a useful knowledge source that benefits many applications in language processing and knowledge representation. An important feature of Wikipedia is that of categories. Wikipedia pages are assigned different categories according to their contents as human-annotated labels which can be used in information retrieval, ad hoc search improvements, entity ranking and tag recommendations. However, important pages are usually assigned too many categories, which makes it difficult to recognize the most important ones that give the best descriptions.   In this paper, we propose an approach to recognize the most descriptive Wikipedia categories. We observe that historical figures in a precise category presumably are mutually similar and such categorical coherence could be evaluated via texts or Wikipedia links of corresponding members in the category. We rank descriptive level of Wikipedia categories according to their coherence and our ranking yield an overall agreement of 88.27% compared with human wisdom.

## Full text

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## Figures

5 figures with captions in the complete paper: https://tomesphere.com/paper/1704.07427/full.md

## References

14 references — full list in the complete paper: https://tomesphere.com/paper/1704.07427/full.md

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Source: https://tomesphere.com/paper/1704.07427