A Survey of Techniques for Constructing Chinese Knowledge Graphs and Their Applications

Abstract

With the continuous development of intelligent technologies, knowledge graph, the backbone of artificial intelligence, has attracted much attention from both academic and industrial communities due to its powerful capability of knowledge representation and reasoning. In recent years, knowledge graph has been widely applied in different kinds of applications, such as semantic search, question answering, knowledge management and so on. Techniques for building Chinese knowledge graphs are also developing rapidly and different Chinese knowledge graphs have been constructed to support various applications. Under the background of the "One Belt One Road (OBOR)" initiative, cooperating with the countries along OBOR on studying knowledge graph techniques and applications will greatly promote the development of artificial intelligence. At the same time, the accumulated experience of China in developing knowledge graphs is also a good reference to develop non-English knowledge graphs. In this paper, we aim to introduce the techniques of constructing Chinese knowledge graphs and their applications, as well as analyse the impact of knowledge graph on OBOR. We first describe the background of OBOR, and then introduce the concept and development history of knowledge graph and typical Chinese knowledge graphs. Afterwards, we present the details of techniques for constructing Chinese knowledge graphs, and demonstrate several applications of Chinese knowledge graphs. Finally, we list some examples to explain the potential impacts of knowledge graph on OBOR.Sustainability 2018, 10, 3245 The Development of Knowledge GraphKnowledge graph is essentially originated from semantic network [3]. Semantic network was proposed in late 1950s and early 1960s, and it is a graph-based data structure to store knowledge, where the graph can be directed or undirected. It is quite convenient to utilize semantic network to represent and store natural language sentences, which can be further applied in machine translation, question answering and natural language understanding. In 1970s, lots of works began to study the relationship between semantic network and first-order predicate. For example, Simmons et al. [4] presented an algorithm to convert semantic network to predicate logic, while Schubert [5] proposed a method leveraging semantic network to represent the conjunctions and quantifiers in first-order predicate logic. In 1980s, the mainstream of artificial intelligence research had become knowledge engineering and expert system, especially rule-based expert system. During this period, the theory of semantic network became more mature and lots of research worked on reasoning based on semantic network [6]. More importantly, the research on semantic network started to turn to knowledge representation and reasoning with strict logical semantics. From late 1980s to 1990s, the research on semantic network focused on modeling the relationship between concepts. Based on this, terminology logic and description logic were proposed. The representative wor...

Does China’s Outward Direct Investment Improve the Institutional Quality of the Belt and Road Countries?

“…While the B&R initiative encompasses many areas of economic integration and global governance [35], it is specifically an infrastructure-led economic integration plan for integrating China's trading partners by developing their infrastructure (i.e., ports, roads, airports, railways, etc.,).The initiative manifests a Chinese commitment to investing in a variety of infrastructure projects in order to strengthen the economic capacity and connectivity among the B&R countries [36]. In the recent past scholars have paid considerable attention to this initiative which has specifically aimed to invest in better connecting Europe, Middle East, Central Asia, South-East Asia, and China [37][38][39][40]. Along with economic integration the B&R initiative is also considered as a vehicle toward sustainable development [41][42][43].…”

Preliminary Study on the Knowledge Graph Construction of Chinese Ancient History and Culture

“…The general domain knowledge graph that is used in this paper is Ownthink and CN-DBpedia. The semi-structured data mainly comes from Baidu Encyclopedia [40], HDWiki [41], taking zhishi.me as an example, Baidu Encyclopedia and Interactive Encyclopedia Chinese Network Encyclopedia are used as data sources for extracting a large amount of knowledge from them to build a knowledge graph [42], for which the semi-structured data are obtained through the use of wrappers, among which the generation methods of wrappers are divided into three categories: manual method, wrapper induction method, and automatic extraction method. In this paper, we mainly used the manual method to analyze and construct the rules of information extraction of the wrapper, so as to obtain the semi-structured data in the web page.…”

Intelligent Interaction with Virtual Geographical Environments Based on Geographic Knowledge Graph

“…Although the linked open data cloud contains some multilingual knowledge graphs, most of the knowledge (including concepts, entities, triples, etc.) is still denoted in English, and the number of Chinese knowledge graphs is quite few [26].…”