Spreadsheet Information Retrieval through Natural Language

The versatility of spreadsheet applications have enabled them to be used for a wide variety of tasks, from inventory management to financial modeling. When they are used for inventory management, extracting additional information can be a difficult task, especially for novice spreadsheet users. Typically, novice users have little experience of using the advanced data processing tools that are available in most spreadsheet applications. To address this issue, the authors propose the use of Natural Language Processing (NLP) techniques to enable such users to perform these tasks. A recent evaluation of NLP-SIR (Natural Language Processing for Spreadsheet Information Retrieval) has shown that natural language can be more effective than conventional data processing tools.

Authors and Affiliations

1. Dundalk Institute of Technology,  

   Derek Flood, Kevin McDaid & Fergal McCaffery

Editors and Affiliations

1. Institut für Computertechnologie, Technische Universität Wien, A-1040, Wien, Austria

   Helmut Horacek

2. CNAM- Laboratoire Cédric, 292 Rue St. Martin, 75141, Paris Cedex 03, France

   Elisabeth Métais

3. Departamento de Lenguajes y Sistemas Informáticos, Universidad de Alicante, Campus de San Vincente del Raspeig, Apdo 99, 03080, Alicante, Spain

   Rafael Muñoz

4. Dept. of Computational Linguistics, Saarland University, Germany

   Magdalena Wolska

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