International Journal of Statistics and Applied Mathematics
  • Printed Journal
  • Indexed Journal
  • Refereed Journal
  • Peer Reviewed Journal
NAAS Journal
Peer Reviewed Journal

2025, Vol. 10, Issue 3, Part A

Future of statistical modeling in information retrieval: A survey


Author(s): Aneesh Kumar K and Reshma PK

Abstract: Information retrieval (IR) is a critical component of modern information systems, aimed at improving the efficiency and relevance of search results. Statistical modeling has a crucial role in the improvement of IR systems, providing methods to rank and retrieve documents based on user queries. This paper surveys the future directions of statistical modeling in IR, focusing on emerging trends, technologies, and methodologies. We explore the convergence of statistical modeling with advancements in machine learning, natural language processing, and big data analytics. Additionally, we address the challenges faced and potential solutions for integrating these advancements into practical IR systems. The survey concludes with a discussion on the anticipated impact of these developments on the field of information retrieval.

DOI: 10.22271/maths.2025.v10.i3a.2000

Pages: 20-22 | Views: 104 | Downloads: 8

Download Full Article: Click Here

International Journal of Statistics and Applied Mathematics
How to cite this article:
Aneesh Kumar K, Reshma PK. Future of statistical modeling in information retrieval: A survey. Int J Stat Appl Math 2025;10(3):20-22. DOI: 10.22271/maths.2025.v10.i3a.2000

Call for book chapter
International Journal of Statistics and Applied Mathematics