TL;DR
This paper introduces an approximate textual retrieval algorithm designed to improve search accuracy in sources with high defect levels by splitting queries and using composite regular expressions.
Contribution
It presents a novel method that balances recall and precision by splitting query words and constructing composite regex patterns to handle defective sources.
Findings
Reduces missed occurrences in defective sources.
Balances retrieval accuracy and relevance.
Improves search robustness in imperfect data sources.
Abstract
An approximate textual retrieval algorithm for searching sources with high levels of defects is presented. It considers splitting the words in a query into two overlapping segments and subsequently building composite regular expressions from interlacing subsets of the segments. This procedure reduces the probability of missed occurrences due to source defects, yet diminishes the retrieval of irrelevant, non-contextual occurrences.
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Taxonomy
TopicsAlgorithms and Data Compression · Web Data Mining and Analysis · Advanced Image and Video Retrieval Techniques