NLP-SIR: A Natural Language Approach for Spreadsheet Information Retrieval

TL;DR

NLP-SIR is a natural language interface designed to simplify spreadsheet data retrieval, making it more accessible especially for novice users, and has demonstrated superior effectiveness over existing tools.

Contribution

This paper introduces NLP-SIR, a novel NLP-based system for spreadsheet information retrieval, and provides an evaluation showing its improved performance.

Findings

NLP-SIR outperforms existing information retrieval tools.

Users find NLP-SIR easier to use for spreadsheet data queries.

Evaluation confirms NLP-SIR's effectiveness in real-world scenarios.

Abstract

Spreadsheets are a ubiquitous software tool, used for a wide variety of tasks such as financial modelling, statistical analysis and inventory management. Extracting meaningful information from such data can be a difficult task, especially for novice users unfamiliar with the advanced data processing features of many spreadsheet applications. We believe that through the use of Natural Language Processing (NLP) techniques this task can be made considerably easier. This paper introduces NLP-SIR, a Natural language interface for spreadsheet information retrieval. The results of a recent evaluation which compared NLP-SIR with existing Information retrieval tools are also outlined. This evaluation has shown that NLP-SIR is a more effective method of spreadsheet information retrieval.