Search Using N-gram Technique Based Statistical Analysis for Knowledge Extraction in Case Based Reasoning Systems
<|reference_start|>Search Using N-gram Technique Based Statistical Analysis for Knowledge Extraction in Case Based Reasoning Systems: Searching techniques for Case Based Reasoning systems involve extensive methods of elimination. In this paper, we look at a new method of arriving at the right solution by performing a series of transformations upon the data. These involve N-gram based comparison and deduction of the input data with the case data, using Morphemes and Phonemes as the deciding parameters. A similar technique for eliminating possible errors using a noise removal function is performed. The error tracking and elimination is performed through a statistical analysis of obtained data, where the entire data set is analyzed as sub-categories of various etymological derivatives. A probability analysis for the closest match is then performed, which yields the final expression. This final expression is referred to the Case Base. The output is redirected through an Expert System based on best possible match. The threshold for the match is customizable, and could be set by the Knowledge-Architect.<|reference_end|>
@article{karthik2004search,
    title={Search Using N-gram Technique Based Statistical Analysis for Knowledge
  Extraction in Case Based Reasoning Systems},
    author={M. N. Karthik and Moshe Davis},
    journal={arXiv preprint arXiv:cs/0407009},
    year={2004},
    archivePrefix={arXiv},
    eprint={cs/0407009},
    primaryClass={cs.AI cs.IR}
}