A comparison of a novel neural spell checker and standard spell checking algorithms

✍ Scribed by Victoria J. Hodge; Jim Austin

• Book ID: 104161537
• Publisher: Elsevier Science
• Year: 2002
• Tongue: English
• Weight: 105 KB
• Volume: 35
• Category: Article
• ISSN: 0031-3203
• DOI: 10.1016/s0031-3203(01)00174-1

✦ Synopsis

In this paper, we propose a simple and exible spell checker using e cient associative matching in the AURA modular neural system. Our approach aims to provide a pre-processor for an information retrieval (IR) system allowing the user's query to be checked against a lexicon and any spelling errors corrected, to prevent wasted searching. IR searching is computationally intensive so much so that if we can prevent futile searches we can minimise computational cost. We evaluate our approach against several commonly used spell checking techniques for memory-use, retrieval speed and recall accuracy. The proposed methodology has low memory use, high speed for word presence checking, reasonable speed for spell checking and a high recall rate.