OKG: On-the-Fly Keyword Generation in Sponsored Search Advertising

Zhao Wang, Briti Gangopadhyay, Mengjie Zhao, Shingo Takamatsu
11/18/2024
cs.IRcs.AI

Official code: sony/okg (6 stars, last commit 2025-02-14).

Abstract

Current keyword decision-making in sponsored search advertising relies on large, static datasets, limiting the ability to automatically set up keywords and adapt to real-time KPI metrics and product updates that are essential for effective advertising. In this paper, we propose On-the-fly Keyword Generation (OKG), an LLM agent-based method that dynamically monitors KPI changes and adapts keyword generation in real time, aligning with strategies recommended by advertising platforms. Additionally, we introduce the first publicly accessible dataset containing real keyword data along with its KPIs across diverse domains, providing a valuable resource for future research. Experimental results show that OKG significantly improves keyword adaptability and responsiveness compared to traditional methods. The code for OKG and the dataset are available at https://github.com/sony/okg.

View on arXivView PDF

Code Implementations(1)

sony/okgOfficial100%

Official Repo for The Paper "OKG: On-the-fly Keyword Generation in Search Sponsered Advertising" (Coling'25)

64Python, Jupyter NotebookNov 15, 20241 years agoNOASSERTION

Similar Papers

Cite this paper

@article{wang2024okg,
  title  = {OKG: On-the-Fly Keyword Generation in Sponsored Search Advertising},
  author = {Zhao Wang and Briti Gangopadhyay and Mengjie Zhao and Shingo Takamatsu},
  year   = {2024},
  eprint = {2412.03577},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2412.03577v1}
}

Add a badge to your README

Shows whether official code is linked for this paper.

Code of Paper badge
[![Code of Paper](https://codeofpaper.com/badge/2412.03577.svg)](https://codeofpaper.com/paper/2412.03577)

Discussion