Achieving High Recall and Precision with HTLM Documents: An Innovation Approach in Information Retrieval

Information retrieval techniques become a challenge to researchers due to huge growth of digital and electronic information. Researchers are attending this area by developing different techniques to enhance precision and recall of retrieved documents. This paper presents an information retrieval system that has promising results in terms of recall and precision. These results are achieved via developing an improved inverted index for the document set and by developing an enhanced evaluation function to evaluate the retrieved documents in response to user query. Results are compared with two well known techniques applied in IR domain which are Okapi-BM25 and Bayesian interface network model and show that precision and recall of the retrieved documents by the proposed method outperforms these two techniques.