KBot: A Knowledge Graph Based ChatBot for Natural Language Understanding Over Linked Data

With the rapid progress of the semantic web, a huge amount of structured data has become available on the web in the form of knowledge bases (KBs). Making these data accessible and useful for end-users is one of the main objectives of chatbots over linked data. Building a chatbot over linked data ra...

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Bibliographic Details
Published in:IEEE access 2020, Vol.8, p.149220-149230
Main Authors: Ait-Mlouk, Addi, Jiang, Lili
Format: Article
Language:English
Subjects:
Chatbot
Chatbots
Computer Science
datalogi
Engines
intent classification
Knowledge
Knowledge based systems
Knowledge bases (artificial intelligence)
Linked Data
Machine learning
Multilingualism
myPersonality dataset
Natural language
natural language understanding
Natural languages
Query processing
Semantic Web
Semantics
Social networks
SPARQL
Task analysis
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Summary:With the rapid progress of the semantic web, a huge amount of structured data has become available on the web in the form of knowledge bases (KBs). Making these data accessible and useful for end-users is one of the main objectives of chatbots over linked data. Building a chatbot over linked data raises different challenges, including user queries understanding, multiple knowledge base support, and multilingual aspect. To address these challenges, we first design and develop an architecture to provide an interactive user interface. Secondly, we propose a machine learning approach based on intent classification and natural language understanding to understand user intents and generate SPARQL queries. We especially process a new social network dataset (i.e., myPersonality) and add it to the existing knowledge bases to extend the chatbot capabilities by understanding analytical queries. The system can be extended with a new domain on-demand, flexible, multiple knowledge base, multilingual, and allows intuitive creation and execution of different tasks for an extensive range of topics. Furthermore, evaluation and application cases in the chatbot are provided to show how it facilitates interactive semantic data towards different real application scenarios and showcase the proposed approach for a knowledge graph and data-driven chatbot.
ISSN:2169-3536
2169-3536
DOI:10.1109/ACCESS.2020.3016142