Title: Technological emergence in the area of personalised advertisement using emergence scoring and topic modelling based on patent data

Authors: Nishad Deshpande; Shabib A. Shaikh; Alok Khode

Addresses: CSIR Unit for Research and Development of Information Products, 'Tapovan' S.No. 113 & 114, NCL Estate Pashan Road, Pune-411008, Maharashtra, India ' CSIR Unit for Research and Development of Information Products, 'Tapovan' S.No. 113 & 114, NCL Estate Pashan Road, Pune-411008, Maharashtra, India ' CSIR Unit for Research and Development of Information Products, 'Tapovan' S.No. 113 & 114, NCL Estate Pashan Road, Pune-411008, Maharashtra, India

Abstract: With the advent of internet, online advertisement has come a long way with personalisation based on user habits, history, etc. as compared to generalised advertisements which many times were considered as spams. The development of sophisticated algorithms and availability of data helps in identification of emerging technologies which in turn can aid technology forecasting and better decision making. Patent is an important techno-legal tool to protect innovations. The developmental aspect of a technology can be studied using patent documents. The current study uses patent dataset to analyse and evaluate patents in the field of personalised advertisement, provides state of the art and also identifies emergent concepts in this domain. The study highlights that the emergence of artificial intelligence and deep learning would drive personalisation along with user interface which may play an important role in customised content delivery as well as user experience for interactive and immersive personalised advertisement.

Keywords: personalised advertising; targeted advertisement; web-based advertisement; patent analysis; technology trends; topic modelling; latent Dirichlet allocation; LDA; technology road-mapping; forecasting; concept emergence.

DOI: 10.1504/IJIMA.2025.148677

International Journal of Internet Marketing and Advertising, 2025 Vol.23 No.3, pp.340 - 360

Received: 22 Feb 2023
Accepted: 22 Jun 2023
Published online: 19 Sep 2025 *

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