Workshop on Knowledge Graph and Natural Language Processing

Scope

Knowledge Graphs are used in several applications such as information retrieval, question answering, data integration, recommendation systems etc., across several domains such as finance, insurance, advertising, logistics, health care, e-commerce and logistics. There are several challenges related to knowledge graphs from the perspective of both the technology and its applications. This workshop aims to foster discussions along these perspectives. a knowledge graph is a large network of entities, their properties, and semantic relationships between entities. Such kind of graph-based knowledge data has been posing a great challenge to the traditional data management theories and technologies.

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Topics

Topics of interest include but are not limited to:

Knowledge graph analysis and applications:
Knowledge graph data visualization
Knowledge-graph based inference and reasoning
Knowledge-graph based information retrieval
Knowledge-graph based recommendation systems
User interfaces of knowledge-graph based systems
Questing answering using knowledge graphs
Knowledge-graph based intelligent systems
Knowledge-graph based information systems
Knowledge graphs and natural language processing

Knowledge graph learning and data mining:
Knowledge graph embedding and representational learning
Graph classification
Graph clustering
Deep learning on knowledge graphs

Workshop Chairs

Haishan Bao, Inner Mongolia University of finance and economics, China

Yana A, Inner Mongolia University of finance and economics, China

Publication

All registered papers will be submitted for publishing by Springer and made available through SpringerLink Digital Library: MobilWare Conference Proceedings.

MobilWare proceedings are indexed in leading indexing services, including Ei Compendex, ISI Web of Science, Scopus, CrossRef, Google Scholar, DBLP, as well as EAI’s own EU Digital Library (EUDL).

Authors of selected best accepted and presented papers will be invited to submit an extended version to: