Data Mining the Content of Food Articles Using Web Crawling

Exploring Association Rules in Web Crawled Food Article Data

Abstract

With the growing internet, searching web is an important part. To retrieve the web pages automatically, web crawler is used. Web crawler feeds on a seed URL and visits all the subsequent URLs to gather information. The processed information is stored in JSON documents. To further find the relationships between web pages, association rule mining is used. The frequent items are found using Apriori algorithm. Association rules are formed using these frequent items. In this paper we proposed a crawler that crawls the recipe site. Then from the structured data of JSON file, association rules are predicted.