A comparison between Entity-Centric Knowledge Base and Knowledge Graph to Represent Semantic Relationships for Searching as Learning Situations

Abstract

Searching the web with learning intent, known as Searching as Learning (SaL), consists on learners to use Web search engines as a technology to drive their learning process. However, it may be difficult to users to find out relevant information online due to an inability to accurately specify their information need, a situation known as Anomalous State of Knowledge (ASK). To minimize the ASK situation, the continuous flow of data gathering and interaction between user and the search results could be used by search engines to tailor learning-intent search experience. It requires Web search engines to identify such intent and they may use linked data, Knowledge Bases and Graph Databases in order to recognize the meaning of query terms and keywords and use them to predict learning intent. In order to explore the possibility of semantic data structures to represent knowledge that could aid a learning-driven Web search engine to recognize learning intention from user's queries, the present paper compared the performance of two different types of data structures based on entity-centric indexing to identify properties and semantic relationships. One was a knowledge base that used a entity-centric mapping of Wikipedia categories and the other was the KBpedia Knowledge Graph. The entity ranking and linking of both were analyzed and we discovered that the knowledge graph could identify about three times more properties and relationships.1 ASK, Anomalous State of Knowledge.

A Probabilistic Model Toward How People Search to Build Outcomes

“…AI methods also allow Searching as Learning to accurately capture changes in cognitive structure. For example, Tibau et al studied the application of knowledge graphs in Searching as Learning situations [20]. Tang et al proved the possibility of applying reinforcement learning to Searching as Learning [21].…”

Uma ontologia para auxílio em ambientes colaborativos para busca de informações

“…Os usuários devem ser acompanhados e orientados sobre o processo de pesquisa à medida que o processo de aprendizagem ocorre [Machado et al 2020]. É comum existir um desconhecimento prévio e incerteza da informac ¸ão, chamado de Anomalous State of Knowledge (ASK), relacionado à incapacidade de especificar com precisão suas necessidades de informac ¸ão [Tibau et al 2019].…”