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The history-based content present on Wikipedia has been used for various NLP-related research. For large-scale analysis, efficient retrieval of past states of Wikipedia is a prerequisite. However, the lack of efficient tools for managing the massive ...

Wikipedia is known for its extensive and comprehensive knowledge of multifarious topics. These topics are maintained as articles along with a history of versions of these articles, these versions are also known as revisions. Revisions are the results ...

The complex collaborative structure of Wikipedia has attracted researchers from various domains, such as social networks, human-computer interaction, and collective intelligence. Yet, a few focus on the readers’ perception of Wikipedia. Readers make up ...

The size of Wikipedia grows exponentially every year, due to which users face the problem of information overload. We purpose a remedy to this problem by developing a recommendation system for Wikipedia articles. The proposed technique automatically ...

Wikipedia articles are known for their exhaustive knowledge and extensive collaboration. Users perform various tasks that include editing in terms of adding new facts or rectifying some mistakes, looking up new topics, or simply browsing. In this paper,...

Wikipedia is an open-content encyclopedia that receives billions of page views per month. It has been observed that in a single reading session, Wikipedia users visit multiple articles. To reduce the problems of overload and loss of information, there ...

Access to knowledge has never been as easy and quick as it has been in the 21st century. With the advent of the Internet and crowd-sourced knowledge building portals such as Wikipedia, Stack Exchange, Quora, and GitHub, information is just a click away. ...

With the success of crowdsourced portals, such as Wikipedia, Stack Overflow, Quora, and GitHub, a class of researchers is driven towards understanding the dynamics of knowledge building on these portals. Even though collaborative knowledge building ...

In this article, we propose an opensource toolkit to extract, parse, and analyze the Wikipedia talk pages. The core parser uses a tree-based approach to parse the unstructured comments and a JSON(JavaScript Object Notation) structure to store them in a ...