Knowledge Graphs

被引：12

作者：

Gutierrez, Claudio ^{[1
,2
]}

Sequeda, Juan F. ^{[3
]}

机构：

[1] Univ Chile, DCC, Santiago, Chile

[2] IMFD, Santiago, Chile

[3] Dataworld, Austin, TX USA

来源：

COMMUNICATIONS OF THE ACM | 2021年 / 64卷 / 03期

关键词：

PRINCIPLES;

D O I：

10.1145/3418294

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

THE NOTION OF Knowledge Graph stems from scientifc advancements in diverse research areas such as Semantic Web, databases, knowledge representation and reasoning, NLP, and machine learning, among others. The integration of ideas and techniques from such disparate disciplines presents a challenge to practitioners and researchers to know how current advances develop from, and are rooted in, early techniques. Understanding the historical context and background of one's research area is of utmost importance in order to understand the possible avenues of the future. Today, this is more important than ever due to the almost infnite sea of information one faces everyday. When it comes to the Knowledge Graph area, we have noticed that students and junior researchers are not completely aware of the source of the ideas, concepts, and techniques they command. © 2021 ACM.

引用

页码：96 / 104

页数：9

共 50 条

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