Meixiang Chen¹, Hong Yang¹, Zhengda Song¹, Yonghua Gu^1,#,*, Yuhong Zheng^1,2, Jiangwei Zhu³, Aiwu Wang⁴, Li Fu^5,#,*

Phyton-International Journal of Experimental Botany, Vol.90, No.5, pp. 1507-1518, 2021, DOI:10.32604/phyton.2021.015723

Abstract Opuntia Milpa Alta is a cactus cultivated, domesticated, hybridized and selected from the plant Opuntia ficus-indica by Mexican agricultural experts, which can be used as fruit and vegetable. Opuntia Milpa Alta leaves and fruit are superior to wild varieties and suitable for storage and transportation. In 1998, Opuntia Milpa Alta was introduced to China from Mexico by the Quality Product Development Center of the Ministry of Agriculture of China. Up to now, the Opuntia Milpa Alta has been cultivated on a certain scale in China. This study aims to identify the research progress and development trends of Opuntia Milpa Alta… More >

Changchun Gao¹, Shiyu Liu^1,*, Chenhui Yu¹, Peng Guo²

Computer Systems Science and Engineering, Vol.38, No.3, pp. 365-379, 2021, DOI:10.32604/csse.2021.016506

Abstract The creative industry is a knowledge-based industry, but it is difficult and complex to create knowledge for enterprises. The principle of cooperation-sharing posits that companies’ limited resources prohibit them from gaining a competitive advantage in all business areas. Therefore, cooperation-sharing can help businesses overcome this hurdle. Cooperation-sharing expedites economic development, breaks the barrier of independent knowledge creation, and enhances resource utilization. However, the effectiveness and stability of knowledge cooperation-sharing are key problems facing governments and other regulators. This study can help regulators promote honesty in enterprise cooperation-sharing. Based on the hypothesis of bounded rationality, the evolutionary game theory was used… More >

Weiyu Guo^1,*, Ruixiang Jia¹, Ying Zhang²

Journal on Artificial Intelligence, Vol.3, No.2, pp. 73-79, 2021, DOI:10.32604/jai.2021.018648

Abstract A knowledge graph consists of a set of interconnected typed entities and their attributes, which shows a better performance to organize, manage and understand knowledge. However, because knowledge graphs contain a lot of knowledge triples, it is difficult to directly display to researchers. Semantic Link Network is an attempt, and it can deal with the construction, representation and reasoning of semantics naturally. Based on the Semantic Link Network, this paper explores the representation and construction of knowledge graph, and develops an academic knowledge graph prototype system to realize the representation, construction and visualization of knowledge graph. More >

Dianqing Liu^1,2, Lanqiu Zhang^1,2, Yanqiu Shao^1,2,*, Junzhao Sun³

Intelligent Automation & Soft Computing, Vol.28, No.2, pp. 447-458, 2021, DOI:10.32604/iasc.2021.016320

Abstract Chinese semantic dependency graph (CSDG) parsing aims to analyze the semantic relationship between words in a sentence. Since it is a deep semantic analysis task, the parser needs a lot of prior knowledge about the real world to distinguish different semantic roles and determine the range of the head nodes of each word. Existing CSDG parsers usually use part-of-speech (POS) and lexical features, which can only provide linguistic knowledge, but not semantic knowledge about the word. To solve this problem, we propose an entity recognition method based on distant supervision and entity classification to recognize entities in sentences, and then… More >

Kun Ding¹, Shanshan Liu¹, Yuhao Zhang², Hui Zhang¹, Xiaoxiong Zhang^1,*, Tongtong Wu^2,3, Xiaolei Zhou¹

CMC-Computers, Materials & Continua, Vol.68, No.1, pp. 377-389, 2021, DOI:10.32604/cmc.2021.016301

Abstract The joint extraction of entities and their relations from certain texts plays a significant role in most natural language processes. For entity and relation extraction in a specific domain, we propose a hybrid neural framework consisting of two parts: a span-based model and a graph-based model. The span-based model can tackle overlapping problems compared with BILOU methods, whereas the graph-based model treats relation prediction as graph classification. Our main contribution is to incorporate external lexical and syntactic knowledge of a specific domain, such as domain dictionaries and dependency structures from texts, into end-to-end neural models. We conducted extensive experiments on… More >

Said Ali Hassan¹, Khalid Alnowibet², Prachi Agrawal³, Ali Wagdy Mohamed^4,5,*

CMC-Computers, Materials & Continua, Vol.68, No.1, pp. 1183-1202, 2021, DOI:10.32604/cmc.2021.015514

Abstract Determining the optimum location of facilities is critical in many fields, particularly in healthcare. This study proposes the application of a suitable location model for field hospitals during the novel coronavirus 2019 (COVID-19) pandemic. The used model is the most appropriate among the three most common location models utilized to solve healthcare problems (the set covering model, the maximal covering model, and the P-median model). The proposed nonlinear binary constrained model is a slight modification of the maximal covering model with a set of nonlinear constraints. The model is used to determine the optimum location of field hospitals for COVID-19… More >

Qi Yue, Xiang Li, Dan Li^*

Computer Systems Science and Engineering, Vol.37, No.3, pp. 423-442, 2021, DOI:10.32604/csse.2021.014448

Abstract Forestry work has long been weak in data integration; its initial state will inevitably affect the forestry project development and decision-quality. Knowledge Graph (KG) can provide better abilities to organize, manage, and understand forestry knowledge. Relation Extraction (RE) is a crucial task of KG construction and information retrieval. Previous researches on relation extraction have proved the performance of using the attention mechanism. However, these methods focused on the representation of the entire sentence and ignored the loss of information. The lack of analysis of words and syntactic features contributes to sentences, especially in Chinese relation extraction, resulting in poor performance.… More >

Yeon-Sun Ahn, Ok-Ran Jeong^*

CMC-Computers, Materials & Continua, Vol.67, No.3, pp. 2695-2708, 2021, DOI:10.32604/cmc.2021.015636

Abstract A knowledge graph is a structured graph in which data obtained from multiple sources are standardized to acquire and integrate human knowledge. Research is being actively conducted to cover a wide variety of knowledge, as it can be applied to applications that help humans. However, existing researches are constructing knowledge graphs without the time information that knowledge implies. Knowledge stored without time information becomes outdated over time, and in the future, the possibility of knowledge being false or meaningful changes is excluded. As a result, they can’t reflect information that changes dynamically, and they can’t accept information that has newly… More >

SoYeop Yoo, OkRan Jeong^*

CMC-Computers, Materials & Continua, Vol.67, No.3, pp. 2807-2817, 2021, DOI:10.32604/cmc.2021.015634

Abstract People occasionally interact with each other through conversation. In particular, we communicate through dialogue and exchange emotions and information from it. Emotions are essential characteristics of natural language. Conversational artificial intelligence is an integral part of all the technologies that allow computers to communicate like humans. For a computer to interact like a human being, it must understand the emotions inherent in the conversation and generate the appropriate responses. However, existing dialogue systems focus only on improving the quality of understanding natural language or generating natural language, excluding emotions. We propose a chatbot based on emotion, which is an essential… More >

BIOCELL Editorial Office

BIOCELL, Vol.45, No.1, pp. 217-227, 2021, DOI:10.32604/biocell.2021.015666

Abstract This article has no abstract. More >