Although primarily an encyclopedia, Wikipedia’s expansive content provides a knowledge base that has been continuously exploited by researchers in a wide variety of domains. This article systematically reviews the scholarly studies that have used Wikipedia as a data source, and investigates the means by which Wikipedia has been employed in three main computer science research areas: information...

In this paper, we introduce the Wikipedia Tools for Google Spreadsheets. Google Spreadsheets is part of a free, Webbased software office suite offered by Google within its Google Docs service. It allows users to create and edit spreadsheets online, while collaborating with other users in realtime. Wikipedia is a free-access, free-content Internet encyclopedia, whose content and data is availabl...

Wikipedia’s link structure is a valuable resource for natural language processing tasks, but only a fraction of the concepts mentioned in each article are annotated with hyperlinks. In this paper, we study how to augment Wikipedia with additional high-precision links. We present 3W, a system that identifies concept mentions in Wikipedia text, and links each mention to its referent page. 3W leve...

Much of work in semantic web relying on Wikipedia as the main source of knowledge often work on static snapshots of the dataset. The full history of Wikipedia revisions, while contains much more useful information, is still difficult to access due to its exceptional volume. To enable further research on this collection, we developed a tool, named Hedera, that efficiently extracts semantic infor...

Abstract. We study the time evolution of ranking and spectral properties of the Google matrix of English Wikipedia hyperlink network during years 2003 2011. The statistical properties of ranking of Wikipedia articles via PageRank and CheiRank probabilities, as well as the matrix spectrum, are shown to be stabilized for 2007 2011. A special emphasis is done on ranking of Wikipedia personalities ...

Wikipedia is the largest organized knowledge repository on the Web, increasingly employed by natural language processing and search tools. In this paper, we investigate the task of labeling Wikipedia pages with standard named entity tags, which can be used further by a range of information extraction and language processing tools. To train the classifiers, we manually annotated a small set of W...

Wikipedia is a “free” online encyclopedia. It contains millions of entries in many languages and is growing at a fast pace. Due to its volume, search engines play an important role in giving access to the information in Wikipedia. The “free” availability of the collection makes it an attractive corpus for information retrieval experiments. In this paper we describe the evaluation of a search en...

Wikis are becoming popular with business and academia as a way to harvest, archive, and manage knowledge. One of the most popular and well-known wikis is Wikipedia, the online encyclopedia started by Jimmy Wales and Larry Sanger in 2001. Since its inception, much has been written (both pro and con) about Wikipedia; however, Wikipedia is one of the most popular sites on the Internet today. As it...

In this paper, we propose a novel method for conceptual hierarchical clustering of documents using knowledge extracted from Wikipedia. The proposed method overcomes the classic bag-of-words models disadvantages through the exploitation of Wikipedia textual content and link structure. A robust and compact document representation is built in real-time using the Wikipedia application programmer’s ...

In this paper we propose a method to automatically label multi-lingual data with named entity tags. We build on prior work utilizing Wikipedia metadata and show how to effectively combine the weak annotations stemming from Wikipedia metadata with information obtained through English-foreign language parallel Wikipedia sentences. The combination is achieved using a novel semi-CRF model for forei...