Keyword Selecting Service for Advertisement
Naver ad keyword recommendation using crawling & AHP weighting
Overview
A keyword recommendation service for advertisers built as a Yonsei University Information Programming course project. The system crawls Naver — Korea's dominant search portal — to identify keywords with the highest blog exposure, then ranks them using AHP (Analytic Hierarchy Process) weighting to help businesses select optimal advertising keywords.
My Role
PM (Project Manager) — led the project, designed the data collection pipeline and ranking methodology, implemented the Java-based crawling and analysis system.
Approach
Given an advertiser's target domain, the system collects related search terms, measures blog exposure for each candidate, and applies multi-criteria AHP analysis to recommend the most cost-effective keywords. Beyond simple data collection, the project explored multiple analytical methods for context-appropriate keyword selection.