Using Machine Learning for Web Page Classification in Search Engine Optimization

Abstract

This paper presents a novel approach of using machine learning algorithms based on experts’ knowledge to classify web pages into three predefined classes according to the degree of content adjustment to the search engine optimization (SEO) recommendations. In this study, classifiers were built and trained to classify an unknown sample (web page) into one of the three predefined classes and to identify important factors that affect the degree of page adjustment. The data in the training set are manually labeled by domain experts. The experimental results show that machine learning can be used for predicting the degree of adjustment of web pages to the SEO recommendations—classifier accuracy ranges from 54.59% to 69.67%, which is higher than the baseline accuracy of classification of samples in the majority class (48.83%). Practical significance of the proposed approach is in providing the core for building software agents and expert systems to automatically detect web pages, or parts of web pages, that need improvement to comply with the SEO guidelines and, therefore, potentially gain higher rankings by search engines. Also, the results of this study contribute to the field of detecting optimal values of ranking factors that search engines use to rank web pages. Experiments in this paper suggest that important factors to be taken into consideration when preparing a web page are page title, meta description, H1 tag (heading), and body text—which is aligned with the findings of previous research. Another result of this research is a new data set of manually labeled web pages that can be used in further research.

Greek Hotels’ Web Traffic: A Comparative Study Based on Search Engine Optimization Techniques and Technologies

“…Search engine optimization (SEO) is the procedure used by SEO specialists to increase both the quality and the number of visitors from search engines to a website [1]. Keywords are words or phrases that online visitors type into search engines while looking for information.…”

“…A meta description including the target keyword might boost SEO results [17]. Websites enriched with metadata are rated higher in search results, than those without metadata [1]. Even when the meta description tag is present on a web page, the description shown on SERPs may differ from website's meta description.…”

“…A website's traffic could be increased in various ways. Organic search, social media, direct, referral, and paid traffic are the most important, according to Google Analytics [1,2]. Users who utilize search engines to locate what they are searching for (free of charge) are the organic traffic.…”

“…Thus, its search engine rankings and organic visitors influence a website's traffic. Since ranking in organic results cannot be paid, a high organic search ranking is in most cases hard to achieve [1]. To rank highly in search engine results, a website must fulfill specific criteria-ranking factors defined in the rules that search engine owners frequently publish [2].…”

Efficient Deep Learning for Reforming Authentic Content Searching on Big Data

“…The search algorithms have been continuously updated again and again since 1998. Big companies like Google tend to improve features that already exist instead of just proceeding with any new innovation [1]. As an example, the companies try to simply revise the ranking algorithms in order to better determine the content quality, instead of using scrapping content quality as the factor for ranking.…”