Spreadsheet Information Retrieval through Natural Language

Abstract

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.