ABSTRACT
ABSTRACT: Document automatic summary is an important research in the field of natural language understanding. Search engines are used nowadays by all Internet users. Keyword selection is a fast-growing industry in which different tools are used by companies to suggest their webpage’s keywords. The research goal of the web automatic summarization technology is to solve this problem directly to provide a concise and comprehensive information page content summary to the user, in order to improve the efficiency of user access to information. It is important to understand how different search engines would choose a webpage in search results based on a user’s query. The paper’s aim is to propose a method that suggests the keywords of a webpage based on frequent terms. The method used in this paper is the term frequency for defining frequent terms. An experiment is executed to validate the method results, and the result of the new method is compared with the Google AdWord tool. The accuracy of the proposed method is 82.4%, which is considered to be a promising result. The experimental results show that the judgment and readability of web page content in this system were superior to the general web page design of automatic summarization.
