Resumen de Relevance of semantic-enriched in information retrieval nodels
Improving document relevance in Information Retrieval has been recently the focus of many research projects and papers. Such investigations and developments are very helpful and essential for everyday private and commercial decisions making process. The main parts of this improvement are the scoring models such as BM25 and the evaluation of the performance of these techniques such as the rank-based models, e.g. MAP, NDCG and RBP. Here we are focusing on the semantic enrichment of the documents using specialised dictionary that will improve the score and rank of the search results. This enrichment is analysed and presented using TREC data and utilizing Lucene full-text search library.
