Tibau, MarceloSiqueira, Sean Wolfgand MatsuiNunes, Bernardo Pereira2025-12-312025-12-319781450388733https://hdl.handle.net/1885/733798363As the amount of information grows exponentially online, Information Systems role in support knowledge flows encouraged by linked data increases as a driver to innovation, culture, business practices and people behavior. Web search engines are particularly affected by the open world challenges, notably as part of the growing digital ecosystems of networks and platforms of technology, media, and telecommunications (TMT) companies delivering personalized and customized services (e.g. Amazon in retailing, Uber in ride service hailing, food delivery, and bicycle-sharing system, and Airbnb in lodging). To recognize search intent drawn from user's behavior allows to provide personalized search results. The work presented in this paper has the purpose of exploring methods to represent semantic relationships between concepts indexed by Web search engines in order to aid them recognize search intent and display results that meet the search intent. The performance of two different types of data structures based on entity-centric indexing was compared. The data structures were: a knowledge base that used an entity-centric mapping of Wikipedia categories and the KBpedia Knowledge Graph. Through analysis of entity ranking and linking, we detected that the Knowledge Graph could identify approximately three times more properties and relationships, which increases Web search engines capability to "understand"what is being asked.This study was financed in part by the “National Council for Scientific and Technological Development (CNPq) - Brazil” - Process 315374/2018-7, Project “Searching as Learning: the information search as a tool for learning” and by the “Coordination for the Improvement of Higher Education Personnel” (CAPES) – Brazil – Finance Code 001.enPublisher Copyright: © 2020 ACM.Entity-centric graph databasesKnowledge graphSearch intentWeb search engine2020-11-0310.1145/3411564.341161185095854077