Query-oriented entity spatial-temporal summarization in fuzzy knowledge graph

Knowledge Graph (KG) is a relatively new concept that has garnered a lot of attention. Furthermore, the information in KG is frequently ambiguous and imprecise, necessitating the creation of a Fuzzy Knowledge Graph (FKG). FKG describes the imprecise information of the entity by employing the fuzzy value of predicates or objects. Entity summarization can extract the most concise and important information from lengthy descriptions of an entity. Existing work, however, focuses solely on entity summarization in KG while ignoring the fuzziness of entity relationships in FKG. Thus, this paper proposed an FFCA-based approach for query-oriented entity spatial-temporal summarization. Fuzzy Formal Concept Analysis (FFCA) is used to turn the FKG into the regular KG initially. The summarized RDF triples can then be obtained by combining the time-centric and location-centric tri-adic concepts from diverse FKGs. Finally, various template-based queries are designed for evaluating the performance of the proposed approach.