Application of Rough Concept Lattice Model in Construction of Ontology and Semantic Annotation in Semantic Web of Things

Xu, Hongsheng; Sun, Huijuan

doi:10.1155/2022/7207372

Cited by 8 publications

(7 citation statements)

References 15 publications

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“…This paper uses the TF-IDF algorithm to extract text features. TF-IDF is a statistical method used to evaluate the importance of a word in a file set or corpus [27]. Its main idea is: if a word appears frequently in one article and rarely in other articles, it is considered that the term has good ability to distinguish and classify, so it can represent the article.…”

Section: Text Feature Extractionmentioning

confidence: 99%

Exploring the Potential of BERT-BiLSTM-CRF and the Attention Mechanism in Building a Tourism Knowledge Graph

Fan

Kuang

et al. 2023

Electronics

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As an important infrastructure in the era of big data, the knowledge graph can integrate and manage data resources. Therefore, the construction of tourism knowledge graphs with wide coverage and of high quality in terms of information from the perspective of tourists’ needs is an effective solution to the problem of information clutter in the tourism field. This paper first analyzes the current state of domestic and international research on constructing tourism knowledge graphs and highlights the problems associated with constructing knowledge graphs, which are that they are time-consuming, laborious and have a single function. In order to make up for these shortcomings, this paper proposes a set of systematic methods to build a tourism knowledge graph. This method integrates the BiLSTM and BERT models and combines these with the attention mechanism. The steps of this methods are as follows: First, data preprocessing is carried out by word segmentation and removing stop words; second, after extracting the features and vectorization of the words, the cosine similarity method is used to classify the tourism text, with the text classification based on naive Bayes being compared through experiments; third, the popular tourism words are obtained through the popularity analysis model. This paper proposes two models to obtain popular words: One is a multi-dimensional tourism product popularity analysis model based on principal component analysis; the other is a popularity analysis model based on emotion analysis; fourth, this paper uses the BiLSTM-CRF model to identify entities and the cosine similarity method to predict the relationship between entities so as to extract high-quality tourism knowledge triplets. In order to improve the effect of entity recognition, this paper proposes entity recognition based on the BiLSTM-LPT and BiLSTM-Hanlp models. The experimental results show that the model can effectively improve the efficiency of entity recognition; finally, a high-quality tourism knowledge was imported into the Neo4j graphic database to build a tourism knowledge graph.

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Section: Text Feature Extractionmentioning

confidence: 99%

Exploring the Potential of BERT-BiLSTM-CRF and the Attention Mechanism in Building a Tourism Knowledge Graph

Fan

Kuang

et al. 2023

Electronics

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“…The horizontal axis represents the six fault types of the current sensor and the average value of labeling accuracy of all fault types. The Precision values of the RCLCA method 6 are 77.35%, 56.23%, 82.16%, 80.49%, 84.74% and 58.82%, respectively, with an average of 73.30%. The Precision values of the SEASOR framework 7 are 62.99%, 79.18%, 85.22%, 67.4%, 56.87% and 85.54%, respectively, with an average of 72.87%.…”

Section: Experimental Evaluationsmentioning

confidence: 99%

Semantic automatic annotation method based on artificial intelligence for electric power internet of things

Jin¹,

Zhang²,

Xue³

et al. 2023

Internet Technology Letters

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The development of the power Internet of Things is currently underway, and a proposal for a semantic Internet of Things based on artificial intelligence algorithms is made to address the challenges in obtaining prior knowledge for heterogeneous data fusion, improving the real‐time performance of the ontology library, and enhancing the efficiency of manual labeling of instance object data in the power field. This proposal introduces an Automatic Semantic Annotation Method to provide an effective knowledge organization model for sensor systems. Data mining knowledge is utilized to drive ontology update and improvement, resulting in more accurate semantic annotation and enhanced machine understanding. Experimental results show that artificial intelligence algorithms can automatically extract concepts from sensory data and achieve automatic semantic annotation during ontology instantiation.

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“…In the context of rural revitalization, rural e-commerce has developed rapidly in recent years, and the rural economy has also been greatly developed, but there are also many problems in the process, such as the weak awareness of rural military and civilian e-commerce, most rural residents believe that e-commerce is a high-tech industry, will only increase their burden, and even think that e-commerce will threaten their livelihoods [9]. Moreover, the income level of most rural residents is not high, let alone the consumption level, so most villagers' understanding of e-commerce still stays on the concept of "online shopping" and do not realize the importance of e-commerce for rural economic development [10].…”

Section: Analysis Of Problems Encountered In the Development Of Rural...mentioning

confidence: 99%

Research on Problems and Suggestions of Rural E-commerce Development under the Background of Rural Revitalization

2023

IJSSEM

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Although rural e-commerce has been developed to a certain extent under the background of rural revitalization, after analysis, it is found that there are also some problems, such as the shortage of e-commerce merchants, and the comprehensive quality is relatively low; E-commerce infrastructure and logistics distribution system are not yet perfect. In view of the above problems, this paper believes that to promote the development of rural e-commerce, we should first establish a sound service system. Secondly, we should constantly improve the construction of rural e-commerce infrastructure. Third, encourage and support e-commerce platforms, express logistics enterprises to carry out e-commerce business. Fourth, we should establish a perfect e-commerce training system. Finally, we must vigorously cultivate and expand rural e-commerce enterprises.

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Application of Rough Concept Lattice Model in Construction of Ontology and Semantic Annotation in Semantic Web of Things

Cited by 8 publications

References 15 publications

Exploring the Potential of BERT-BiLSTM-CRF and the Attention Mechanism in Building a Tourism Knowledge Graph

Exploring the Potential of BERT-BiLSTM-CRF and the Attention Mechanism in Building a Tourism Knowledge Graph

Semantic automatic annotation method based on artificial intelligence for electric power internet of things

Research on Problems and Suggestions of Rural E-commerce Development under the Background of Rural Revitalization

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