[Corpora-List] Artificial Intelligence Journal Special Issue on "AI, Wikipedia and Semi-Structured Resources" now online!

Roberto Navigli navigli at di.uniroma1.it
Thu Dec 6 08:10:14 CET 2012

Dear colleagues,

we are delighted to announce the publication of the Artificial Intelligence Journal Special Issue on "Artificial Intelligence, Wikipedia and Semi-Structured Resources". This Special Issue aims at providing a comprehensive picture of the state of the art of research that exploits semi-structured resources (Wikipedia, most notably) for Artificial Intelligence (AI) and Natural Language Processing (NLP). The issue is the result of a highly selective publication process which involved more than 70 submissions and 100 reviewers: as a result, it presents a series of top-research contributions, which together provide a comprehensive and up-to-date overview of the many different lines of research that have been, and are being, pursued in this highly active area of investigation.

All papers can be accessed from the Artificial Intelligence Journal web-page (see under either "View Articles" or "Special Issues")


or accessed directly via Elsevier's ScienceDirect system


Please note that the AI Journal can be accessed free of charge following the instructions found here:


We wish you to enjoy the papers and hope that you will find them useful in your own research!

The AI Journal Special Issue Guest Editors:

Eduard Hovy, Roberto Navigli and Simone Paolo Ponzetto


Artificial Intelligence, Volume 194, Pages 1-252 (January 2013) TABLE OF CONTENTS

Eduard Hovy, Roberto Navigli, Simone Paolo Ponzetto: Editorial (p. 1).

- Introduction

Eduard Hovy, Roberto Navigli, Simone Paolo Ponzetto: Collaboratively built semi-structured content and Artificial Intelligence: The story so far (pp. 2-27).

- Acquiring knowledge

Johannes Hoffart, Fabian M. Suchanek, Klaus Berberich, Gerhard Weikum: YAGO2: A spatially and temporally enhanced knowledge base from Wikipedia (pp. 28-61).

Vivi Nastase, Michael Strube: Transforming Wikipedia into a large scale multilingual concept network (pp. 62-85).

- IR applications

Pekka Malo, Pyry Siitari, Ankur Sinha: Automated query learning with Wikipedia and genetic programming (pp. 86-110).

Rianne Kaptein, Jaap Kamps: Exploiting the category structure of Wikipedia for entity ranking (pp. 111-129).

- NLP applications

Ben Hachey, Will Radford, Joel Nothman, Matthew Honnibal, James R. Curran: Evaluating Entity Linking with Wikipedia (pp. 130-150).

Joel Nothman, Nicky Ringland, Will Radford, Tara Murphy, James R. Curran: Learning multilingual named entity recognition from Wikipedia (pp. 151-175).

Majid Yazdani, Andrei Popescu-Belis: Computing text semantic relatedness using the contents and links of a hypertext encyclopedia (pp. 176-202).

Sara Tonelli, Claudio Giuliano, Kateryna Tymoshenko: Wikipedia-based WSD for multilingual frame annotation (pp. 203-221).

- Tools

David Milne, Ian H. Witten: An open-source toolkit for mining Wikipedia (pp. 222-239).

- Neuroimaging

Francisco Pereira, Matthew Botvinick, Greg Detre: Using Wikipedia to learn semantic feature representations of concrete concepts in neuroimaging experiments (pp. 240-252).

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