Chinese-Uyghur-English Semantic Search Based on the Knowledge Graphs
Lirong Qiu, Na Yang, Maierdan Maolimamuti · 2017
Semantic search is becoming a more independent search engine, which is capable of analyzing independently, understanding the essential needs and providing accurate answers. In this work, the basis of analyzing the content framework puts forward the theory on the basis of knowledge graph. In the semantic web, search engines use a knowledge graph to identify the query involved in the entity and its attributes, giving a precise answer by efficient web search. Based on the semantic web, we proposed the K-means algorithm that applied to construct knowledge graph, will be sorted in knowledge bases by classifying similarity word, building Uygur's knowledge graph architecture, and then, take the built knowledge graph to show the semantic searching.