Crossover improvement for the genetic algorithm in information retrieval
Information Processing and Management: an International Journal
Using genetic algorithms to find suboptimal retrieval expert combinations
Proceedings of the 2002 ACM symposium on Applied computing
A test of genetic algorithms in relevance feedback
Information Processing and Management: an International Journal
Genetic Mining of HTML Structures for Effective Web-Document Retrieval
Applied Intelligence
A New Study on Using HTML Structures to Improve Retrieval
ICTAI '99 Proceedings of the 11th IEEE International Conference on Tools with Artificial Intelligence
Journal of the American Society for Information Science and Technology
Expert Systems with Applications: An International Journal
Genetic Algorithm Based to Improve HTML Document Retrieval
DESE '09 Proceedings of the 2009 Second International Conference on Developments in eSystems Engineering
Using genetic algorithms for data mining optimization in an educational web-based system
GECCO'03 Proceedings of the 2003 international conference on Genetic and evolutionary computation: PartII
Improving web retrieval precision based on semantic relationships and proximity of query keywords
DEXA'06 Proceedings of the 17th international conference on Database and Expert Systems Applications
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Increasing the growth rates of websites' number has led to the challenge of assisting Web customers in finding appropriate details from the Internet using an intelligent search engine. Information retrieval IR is an essential and useful strategy for Web users; thus, different strategies and techniques are designed for such purpose. Currently, the focus on the usefulness of Artificial Intelligence AI has been improved with IR. One AI area is Evolutionary Computation EC, which is based on designs of natural selection. A traditional and important strategy in EC is Genetic Algorithm GA; this paper adopts the GA technique to enhance the retrieval of HTML documents. This improvement is obtained by creating a modern evaluation function and applying a hybrid crossover operator. The proposed evaluation function is based on term proximity, keyword probability within the document, and HTML tag weight query. Experimental results are compared with two well known evaluation function functions applied in IR domain which are Okapi-BM25 and Bayesian interface network model. The results demonstrate a good level of enhancement to the recall and precision. In addition, the documents retrieved by the proposed system were more accurate and relevant to the queries than that retrieved by other models.