Genetic algorithm-based rule generation for approximate keyword search
by M. Priya; R. Kalpana
International Journal of Advanced Intelligence Paradigms (IJAIP), Vol. 25, No. 3/4, 2023

Abstract: A lot of problems with natural language processing, data mining, information retrieval and bioinformatics can be legitimated as trying transformation. The task of the string transformation is, once the input string is given, the system generates the k most likely occurring output strings resultant to the input string. The existing method for approximate keyword search based on rules uses two processes called learning and generation which provides the improvement in both accuracy and efficiency of searching, but not to the expected level. A new genetic algorithm-based approach is introduced to generate rules and the generated rules are learned by applying maximum-a-likelihood function to select the best rule and produce a rule dictionary. The given query keyword is searched in database by constructing tree-based index called Aho-Corasick tree and carry out the pattern matching with the rule dictionary for retrieving the document even if it has some misspelling. The experimental result shows better enhancement in terms of both accuracy and efficiency when compared to existing methods.

Online publication date: Wed, 19-Jul-2023

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Advanced Intelligence Paradigms (IJAIP):
Login with your Inderscience username and password:

    Username:        Password:         

Forgotten your password?

Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email