Abstract
Information retrieval is the study of finding relevant information from the semi-unstructured type of data. This paper surveys the insightful techniques and shows the comparative analysis between several information retrieval systems using machine learning approach. Information that we get from the web portal should be with high recall and high precision and F-measure. In this paper, in order to compare information retrieval techniques, we use these parameters like recall, precision, accuracy, and so on. Recall means the ability of the system to retrieve all relevant documents. High precision means the ability of the system to retrieve only relevant documents. F-measure is a proportion of a test’s accuracy. To compute the score it considers both the recall and the precision.
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Solanki, S., Verma, S., Chahar, K. (2020). A Comparative Study of Information Retrieval Using Machine Learning. In: Sharma, H., Govindan, K., Poonia, R., Kumar, S., El-Medany, W. (eds) Advances in Computing and Intelligent Systems. Algorithms for Intelligent Systems. Springer, Singapore. https://doi.org/10.1007/978-981-15-0222-4_3
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DOI: https://doi.org/10.1007/978-981-15-0222-4_3
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