Empowering things with intelligence: a survey of the progress, challenges, and opportunities in artificial intelligence of things
In the Internet-of-Things (IoT) era, billions of sensors and devices collect and process data
from the environment, transmit them to cloud centers, and receive feedback via the Internet …
from the environment, transmit them to cloud centers, and receive feedback via the Internet …
Defining a knowledge graph development process through a systematic review
G Tamašauskaitė, P Groth - ACM Transactions on Software Engineering …, 2023 - dl.acm.org
Knowledge graphs are widely used in industry and studied within the academic community.
However, the models applied in the development of knowledge graphs vary. Analysing and …
However, the models applied in the development of knowledge graphs vary. Analysing and …
Recent trends in knowledge graphs: theory and practice
S Tiwari, FN Al-Aswadi, D Gaurav - Soft Computing, 2021 - Springer
With the extensive growth of data that has been joined with the thriving development of the
Internet in this century, finding or getting valuable information and knowledge from these …
Internet in this century, finding or getting valuable information and knowledge from these …
Data-driven analysis and machine learning-based crop and fertilizer recommendation system for revolutionizing farming practices
C Musanase, A Vodacek, D Hanyurwimfura… - Agriculture, 2023 - mdpi.com
Agriculture plays a key role in global food security. Agriculture is critical to global food
security and economic development. Precision farming using machine learning (ML) and the …
security and economic development. Precision farming using machine learning (ML) and the …
Building knowledge graphs from unstructured texts: Applications and impact analyses in cybersecurity education
Knowledge graphs gained popularity in recent years and have been useful for concept
visualization and contextual information retrieval in various applications. However …
visualization and contextual information retrieval in various applications. However …
Applications of knowledge graphs for food science and industry
The deployment of various networks (eg, Internet of Things [IoT] and mobile networks),
databases (eg, nutrition tables and food compositional databases), and social media (eg …
databases (eg, nutrition tables and food compositional databases), and social media (eg …
Integrating entity attributes for error-aware knowledge graph embedding
Knowledge graphs (KGs) can structurally organize large-scale information in the form of
triples and significantly support many real-world applications. While most KG embedding …
triples and significantly support many real-world applications. While most KG embedding …
Agi for agriculture
Artificial General Intelligence (AGI) is poised to revolutionize a variety of sectors, including
healthcare, finance, transportation, and education. Within healthcare, AGI is being utilized to …
healthcare, finance, transportation, and education. Within healthcare, AGI is being utilized to …
AgCNER, the first large-scale Chinese named entity recognition dataset for agricultural diseases and pests
Named entity recognition is a fundamental subtask for knowledge graph construction and
question-answering in the agricultural diseases and pests field. Although several works …
question-answering in the agricultural diseases and pests field. Although several works …
结合知识图谱与双向长短时记忆网络的小麦条锈病预测.
张善文， 王振， 王祖良 - … of the Chinese Society of Agricultural …, 2020 - search.ebscohost.com
针对现有小麦条锈病预测方法没有利用病害发生因素之间的语义信息, 存在预测难度大,
准确率低等问题, 利用知识图谱(Knowledge Graph, KG) 和双向长短时记忆网络(Bi-directional …
准确率低等问题, 利用知识图谱(Knowledge Graph, KG) 和双向长短时记忆网络(Bi-directional …