Research on Semantic Retrieval System for the Document Knowledge Based on Domain Ontology

Liu, Zi Yu; Zhang, Dong Li; Li, Xue Hui

doi:10.4028/www.scientific.net/amr.204-210.2171

Cited by 6 publications

(4 citation statements)

References 1 publication

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“…Researchers have proposed various effective patent semantic retrieval algorithms by combining semantic retrieval methods with traditional patent retrieval algorithms [13,14]. The semantic retrieval of patent literature usually processes the patent text and then matches the similarity through classification algorithms, which mainly includes the collection of patent text information, the preprocessing of patent text information, the classification of patent text, and the calculation of patent text semantic similarity [15].…”

Section: Semantics-based Patent Retrieval Methodsmentioning

confidence: 99%

Methods for the Intellectual Properties Retrieval from Patents

Xu¹,

Zhu²,

Wang³

et al. 2023

Atlantis Highlights in Intelligent Systems

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With the increasing requirements to protect intellectual property, more and more attention is paid to the research of patent strategy. Intellectual propertyoriented patent search is different from normal literature retrieval as its with professional field characteristics and diversified information retrieval. Therefore, this paper first summarizes the main research status of traditional information-based patent retrieval methods, semantic-based patent retrieval methods and knowledge graph-based patent retrieval methods, and then introduces representative patent retrieval applications. Finally, it suggested some ideas for further research on intellectual properties search from patents by discussing the application of deep learning in patent retrieval.

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Section: Semantics-based Patent Retrieval Methodsmentioning

confidence: 99%

Methods for the Intellectual Properties Retrieval from Patents

Xu¹,

Zhu²,

Wang³

et al. 2023

Atlantis Highlights in Intelligent Systems

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“…In the direction of the formal representation of industrial domain knowledge, the key technical means involved contain the predicate logic knowledge representation method [22], the frameworkbased knowledge representation method [23], the semantic network-based knowledge representation method [24], and the ontology-based knowledge representation method [25]. The current representative works on ontology-based knowledge representation methods in the industrial domain include the following: for product design process knowledge and manufacturing process knowledge, Chhim et al developed ontologies that unite the two types of knowledge and tried to apply them to the knowledge reuse process; for process design knowledge [16], Guo et al considered the process knowledge characteristics and domain scope [25] and proposed a logical architecture of process knowledge management based on ontology; for the whole life cycle knowledge of the manufacturing domain, Liu et al [26] proposed a multi-level and multidimensional knowledge expression model based on ontology to realize the structured and dimensional representation of manufacturing domain knowledge; and for collaborative design knowledge, Bock et al explored the method of combining ontology and model-based technology for collaborative design [27].…”

Section: Knowledge Graphmentioning

confidence: 99%

A Study on a Knowledge Graph Construction Method of Safety Reports for Process Industries

et al. 2023

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There are some representative reports in industrial safety engineering, such as the Hazard and Operability Analysis and Pre-Hazard Analysis; however, a large amount of industrial safety knowledge in the report has not been fully explored. In order to reuse and release the value of industrial safety knowledge, this paper constructs a new industrial safety knowledge extraction framework. The framework combines the asset management shell to summarize the knowledge concept entities of machine description language and model description language. According to the safety report template, the framework also constructs a new industrial safety knowledge-mapping standard structure. Specifically, firstly, considering that the knowledge structure of safety reports is different in different processes of the process industry, this paper innovatively proposes a general industrial safety knowledge-mapping standard structure, which provides a practical solution for the integration of industrial knowledge representation problems in different processes. Secondly, based on the research progress of named entities, this paper presents an industrial named entity extraction method (INERM) for the process industry. This method designs an entity weight model to calculate the entity weight of each sentence, and adds part-of-speech weight to improve the entity extraction algorithm, which alleviates the problem that the existing entity extraction methods cannot reasonably use the semantic information and context of word. Finally, we construct a triple of industrial safety knowledge based on the rules and store it in Neo4j. In this paper, four semantic-type templates and five semantic relation templates are constructed based on the new industrial safety knowledge map standardization construction process of the process industry. The comparative experiments show that the accuracy of the INERM on the test set is improved by 17 percentage points on average compared with other key entity extraction algorithms. A total of 1329 entities are constructed in the directional application example of the fluid transportation process, which provides a large number of references for the safety of the fluid transportation process and is more conducive to improving the safety guarantee of the fluid transport process.

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“…The semantic extension method based on ontology is adopted to solve this problem. In [19], a comprehensive semantic similarity algorithm based on ontology is proposed to solve the problem of low efficiency of traditional knowledge retrieval. On the basis of this algorithm, an improved semantic extension method based on ontology concept relation, concept depth, concept density and concept attribute is proposed to expand the semantic extension of user retrieval keywords and knowledge index.…”

Section: Ontology-based Semantic Extension a Semantic Extension mentioning

confidence: 99%

Manufacturing Technology Knowledge Retrieval System Based on OSE and UCF

et al. 2019

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Nowadays it is commonly accepted that knowledge, as a resource has become increasingly important in the drive toward knowledge-driven innovation in the manufacturing industry, and which is especially critical for the research and development of complex equipment. In China, there are several fields of manufacturing, such as aviation, ship, and electronics. Although each of them has its own professional technology, they also take advantage of the basic common manufacturing technology. Thus, it is meant for sharing manufacturing technology knowledge. In order to promote innovation, a manufacturing technology knowledge retrieval system is developed to make more efficient use of manufacturing technology knowledge. Manufacturing technology knowledge is a phrase with vast meanings, which may include knowledge of different manufacturing process means, machine, and process capabilities or the latest technology developments. In this system, the manufacturing technology knowledge is defined and organized. A knowledge retrieval method based on the weighted fusion of ontology-based semantic extension (OSE) and user-based collaborative filtering (UCF) is proposed and described detailed. On this basis, the prototype system of manufacturing technology knowledge retrieval system is developed. Its architecture and main functions are elaborated. The results of this system facilitate the sharing of manufacturing knowledge, and it is expected to accelerate the process of knowledge transfer, to improve the level of the overall manufacturing technology. INDEX TERMS Manufacturing technology knowledge, ontology-based semantic extension, user-based collaborative filtering, knowledge sharing.

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Research on Semantic Retrieval System for the Document Knowledge Based on Domain Ontology

Cited by 6 publications

References 1 publication

Methods for the Intellectual Properties Retrieval from Patents

Methods for the Intellectual Properties Retrieval from Patents

A Study on a Knowledge Graph Construction Method of Safety Reports for Process Industries

Manufacturing Technology Knowledge Retrieval System Based on OSE and UCF

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