DocumentCode
134254
Title
An ontology semantic tree based natural language interface
Author
Shusen Li ; Zhiyang He ; Ji Wu
Author_Institution
Dept. of Electron. Eng., Tsinghua Univ., Beijing, China
fYear
2014
fDate
12-14 Sept. 2014
Firstpage
226
Lastpage
230
Abstract
As more and more ontology knowledge bases have been published, every user may have access to a wealth of knowledge. However, to acquire the information in ontologies, users have to be familiar with ontologies and its formal query language. Therefore, natural language interfaces (NLI) have been proposed in recent years to bridge the gap between ontologies and non-expert users. Traditional approaches have pretty broad coverage of natural language (NL) and good performance on wellorganised NL queries. But they are subject to the word order, due to the lack of original semantic information of queries. This paper proposes a NLI which accepts NL as input and generates SPARQL (SPARQL Protocol and RDF Query Language) queries as output. To analyze the NL queries, the ontology semantic tree has been used to represent the semantic conceptual structure of NL queries with the support of ontology. Our results show that the proposed system can make use of semantic structure effectively and has a better performance than the baseline system on the queries with flexible word order.
Keywords
natural language interfaces; ontologies (artificial intelligence); query languages; query processing; NL coverage; NL query; NLI; RDF query language; SPARQL; SPARQL protocol; information acquisition; natural language interface; ontology knowledge base; ontology semantic tree; semantic information; word order; Database languages; Knowledge based systems; Natural languages; Ontologies; Resource description framework; Semantics; SPARQL; natural language interface; ontology semantic tree;
fLanguage
English
Publisher
ieee
Conference_Titel
Chinese Spoken Language Processing (ISCSLP), 2014 9th International Symposium on
Conference_Location
Singapore
Type
conf
DOI
10.1109/ISCSLP.2014.6936647
Filename
6936647
Link To Document