Context-Based Model for Browsing the Web Through Voice

To find useful information on the Web, a user must define the search according to their interests, then they must select and analyze one or more web pages, and finally they must decide which content is most useful to them. This process requires visual attention, certain skills, and interaction with the web browser through keyboards, screens, or mice. Web browsing can be difficult for people who have some disability or lack of knowledge in the use of information and communications technology, causing them to stop this activity. This paper proposes a model to facilitate web browsing and contribute to reducing the digital divide among the population. The model input is the user’s request in natural language using voice, and the output, presented in sound, text, or graphic format, is the most suitable content that corresponds to the user’s interests. First, a content search is performed based on the user’s context. Subsequently, among the results obtained, the most appropriate for the user are identified by analyzing the context of web pages. We implemented a prototype, which was evaluated by users. The results show that it reached an acceptable usability level and that 84.75% of users obtained relevant results in their interactions.