Keyword Extraction for Search Engine Optimization Using Latent Semantic Analysis

Abstract

It is now difficult to access desired information in the Internet world. Search engines are always trying to overcome this difficulty. However, web pages that cannot reach their target audience in search engines cannot become popular. For this reason, search engine optimization is done to increase the visibility in search engines. In this process, a few keywords are selected from the textual content added to the web page. A responsible person who is knowledgeable about the content and search engine optimization is required to determine these words. Otherwise, an effective optimization study cannot be obtained. In this study, the keyword extraction from textual data with latent semantic analysis technique was performed. The latent semantic analysis technique models the relations between documents/sentences and terms in the text using linear algebra. According to the similarity values of the terms in the resulting vector space, the words that best represent the text are listed. This allows people without knowledge of the SEO process and content to add content that complies with the SEO criteria. Thus, with this method, both financial expenses are reduced and the opportunity to reach the target audience of web pages is provided.