An Approach to Improve Precision and Recall for Ad-hoc Information Retrieval Using SBIR Algorithm

Information Retrieval is a process of finding the documents in a collection based on a specific topic. The information need is expressed by the user as a query. Documents that satisfy the given query in the judgment of the user are said to be relevant. The documents that are not of the given topic are said to be non-relevant. An IR engine may use the query to classify the documents in a collection, returning to the user a subset of documents that satisfy some classification criterion. There are several search engines to find information in the given repositories containing large amounts of unstructured form of text data. However, the task of ad hoc information retrieval is, finding documents within a corpus like Bible, that are relevant to the user remains a hard challenge. Sometimes the relevant documents may not contain the specified keyword. The lack of the given term in a document does not necessarily mean that the document is not a relevant. Because more than one terms can be semantically similar although they are lexicographically different. In this paper a new algorithm called "Semantic based Boolean Information Retrieval" (SBIR) is proposed to retrieve the documents with semantically similar terms to enhance the performance of Boolean Information Model by improving the recall and precision.