• Muzafar Rasool Bhat

Different algebraic model-based information retrieval algorithms produce different retrieval results and have different efficiencies. For extending studies in information retrieval, a researcher often requires detailed comparison of results produced by different algorithms. Using Precision and Recall tests, this paper evaluates efficiency of three main algebraic model-based information retrieval algorithms namely TFIDF, VSM and LSI. Suitability of these algorithms for small and large data collections is analyzed. We have used text collections MED and CACM in this research. A simple algorithm for extraction of terms and identifying stop words is proposed. This work uses term frequencies procedure for weighing extracted terms. It further studies impact on efficiency of LSI by using varying number of singular values from 50 to 250.

information retrieval, TFIDF, VSM, LSI.

"Evaluating Algebraic Model Based Information Retrieval Algorithms for Small and Large Data set ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 5, page no.55-62, May 2019, Available :http://www.jetir.org/papers/JETIR1905Y08.pdf

"Evaluating Algebraic Model Based Information Retrieval Algorithms for Small and Large Data set ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 5, page no. pp55-62, May 2019, Available at : http://www.jetir.org/papers/JETIR1905Y08.pdf