Exploiting Artificial Immune System to Optimize Association Rules for Word Sense Disambiguation
DOI:
https://doi.org/10.18201/ijisae.2021473638Keywords:
Artificial Immune System, Association Rule Mining, Lexical Ambiguity, Word Sense DisambiguationAbstract
Requirement specification is the major activity in software development. Since requirements are gathered from the customers in natural languages they are prone to ambiguities. Ambiguous requirements give many interpretations of the same word or sentence. In order to reduce the problems faced due to requirement ambiguities, many techniques have been proposed in the past. To reduce the ambiguities and optimize the association mining rules for WSD, this paper proposes a new approach based on Artificial Immune System and Association Rule Mining. The approach shows significant results when tested on a collection of many Software Requirement Specifications (SRS) Documents. The average accuracy provided by the system is 89.2725%. outperforms state of the art methods.
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