CN112307772B - Construction method of broad-color porcelain knowledge base based on semantic ontology - Google Patents
Construction method of broad-color porcelain knowledge base based on semantic ontology Download PDFInfo
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Abstract
The application discloses a construction method of a broad-color porcelain knowledge base based on a semantic ontology, which comprises the following steps: performing semantic analysis on the Guangdong porcelain elements according to the Guangdong porcelain patterns, and constructing a modeling primitive language of a semantic ontology; acquiring explicit knowledge and implicit knowledge of the colorful porcelain knowledge according to a knowledge management principle; dividing a library corresponding to the explicit knowledge and the implicit knowledge into a general knowledge ontology, a dynamic knowledge ontology and a domain knowledge ontology; fusing a general knowledge ontology, a dynamic knowledge ontology and a domain knowledge ontology into a colorful porcelain knowledge model; and constructing a semantic retrieval model for personalized learning based on the Guangdong porcelain knowledge model. The modeling meta-language of the multi-dimensional semantic body is combined with the semantic analysis of the Guangdong color porcelain element, the Guangdong color porcelain knowledge model and the semantic retrieval model of the multi-dimensional semantic body are constructed from the knowledge application angle, and the practicability and the usability of the Guangdong color porcelain knowledge base are enhanced.
Description
Technical Field
The application relates to the technical field of knowledge bases, in particular to a construction method of a broad-color porcelain knowledge base based on semantic ontology.
Background
Semantic ontologies are formal specifications of the display of a shared conceptual model, with the goal of transforming a cluttered information source into an ordered and easy-to-use knowledge source. The semantic ontology is the core concept of the semantic network, wherein the core of the semantic is the knowledge sharing. Ontology is widely concerned in the field of information science as an effective form of knowledge organization, and the ontology idea is introduced into the information science to hopefully describe and organize information on semantic and knowledge levels and provide semantic basis for common understanding of knowledge by computers. The semantic ontology is a new research direction in academic circles, and by adopting the semantic ontology research method, an element semantic description system and element research in a certain field can be comprehensively constructed, so that the semantic ontology has good reproducibility and is beneficial to systematic construction of different field cultures.
Currently, the learners further derive and expand the semantic system on the basis of building the Huizhou folk house feature description system by a semantic ontology method. The HOZO software is used for exporting the constructed codes of the constructed semantic system, models of different physiognomic elements in the system are manufactured, the codes are endowed with graphical information through programming, the constructed system codes and the models are superposed, and a model database of the Huizhou folk house physiognomic elements can be established.
At present, most of designs for constructing database models based on semantic ontology theory are mainly based on how to construct database models, and further application consideration to the database models is lacked in the construction process, so that the constructed knowledge base models have application limitation.
Disclosure of Invention
The application provides a construction method of a broad-color porcelain knowledge base based on a semantic ontology, which is used for solving the technical problem that the constructed knowledge base model has application limitation because the prior art lacks consideration on further application of a database model.
In view of this, the present application provides a method for constructing a broad-color porcelain knowledge base based on a semantic ontology, where the method includes:
performing semantic analysis on the Guangdong porcelain elements according to the Guangdong porcelain patterns, and constructing a modeling primitive language of a semantic ontology;
acquiring explicit knowledge and implicit knowledge of the colorful porcelain knowledge according to a knowledge management principle;
dividing the library corresponding to the explicit knowledge and the implicit knowledge into a general knowledge ontology, a dynamic knowledge ontology and a domain knowledge ontology;
fusing a general knowledge ontology, a dynamic knowledge ontology and a domain knowledge ontology into a colorful porcelain knowledge model;
and constructing a semantic retrieval model for personalized learning based on the Guangdong porcelain knowledge model.
Preferably, the semantic analysis is performed on the wide color porcelain elements, and the wide color porcelain elements include: the shape, color, elements and theme of the colorful porcelain works.
Preferably, the modeling primitive comprises: class, relationship, function, axiom, instance, terms and concepts related to the field of the class of the Guangdong colored porcelain;
the relationship comprises an object relationship attribute and a value relationship attribute;
the function is used for describing the relationship between the concept and the data type;
the instance is a representation of an object.
Preferably, the concepts include a primary concept and a secondary concept, the concept represents a set of objects, the relationship pair represents a set of object tuples, and the concepts adopt a framework structure and include names of the concepts, sets of relationships with other concepts, and descriptions of the concepts by semantics.
Preferably, the library corresponding to the implicit knowledge comprises a knowledge base, wherein the knowledge base comprises semantic ontology knowledge information and corresponding pattern information; the library corresponding to the explicit knowledge comprises a case sample library which comprises images, texts, audios and videos of the Guangxi porcelain.
Preferably, the general ontology comprises general concepts of: the history, process, color and border of the porcelain with the colorful porcelain.
Preferably, the domain ontology refers to knowledge describing a specific application domain and subject.
Preferably, the ontology of dynamic knowledge is drawn by the actual requirements of the user, the construction process is automatically completed by a machine by using the existing knowledge and network data resources, and the ontology of dynamic knowledge mainly focuses on objects and relationships among the objects in a specific task, event or activity.
Preferably, the search process of the semantic search model includes the following steps:
acquiring a user request, and extracting a semantic tag according to the user request;
performing information reasoning according to the semantic tags to perform extended query on the Guangdong porcelain knowledge model;
and screening the retrieval result and pushing the retrieval result to the user.
Preferably, the process of performing personality learning through the semantic retrieval model includes:
generating image description according to the semantic retrieval result;
and carrying out the configuration extraction and reuse of the wide color porcelain according to the image description.
The application provides a construction method of a broad-color porcelain knowledge base based on a semantic ontology, which comprises the following steps: performing semantic analysis on the Guangdong porcelain elements according to the Guangdong porcelain patterns, and constructing a modeling primitive language of a semantic ontology; acquiring explicit knowledge and implicit knowledge of the colorful porcelain knowledge according to a knowledge management principle; dividing the library corresponding to the explicit knowledge and the implicit knowledge into a general knowledge ontology, a dynamic knowledge ontology and a domain knowledge ontology; fusing a general knowledge ontology, a dynamic knowledge ontology and a domain knowledge ontology into a colorful porcelain knowledge model; and constructing a semantic retrieval model for personalized learning based on the Guangdong porcelain knowledge model.
This application combines the modeling primitive language of body through the elementary language to the Guangdong color porcelain element semanteme, has constructed the Guangdong color porcelain knowledge model and the semantic retrieval model of multidimension semanteme body from the angle that knowledge was used, has strengthened the practicality and the ease for use of Guangdong color porcelain knowledge base, can promote people to traditional culture's propagation and study, further provides new way for the study inheritance that people participated in traditional culture.
Drawings
FIG. 1 is a flowchart of an embodiment of a construction method of a semantic ontology-based Guangdong china knowledge base according to the present application;
FIG. 2 is a flowchart of another embodiment of a construction method of a semantic ontology-based Guangcolou porcelain knowledge base according to the present application;
fig. 3 is a flowchart of another embodiment of the method for constructing a semantic ontology-based cantonese knowledge base according to the present application.
Detailed Description
In order to make the technical solutions of the present application better understood, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
Please refer to fig. 1, which is a flowchart illustrating an embodiment of a method for constructing a semantic ontology-based lottery knowledge base according to the present application, including the following steps:
s100, performing semantic analysis on the Guangdong color porcelain elements according to the Guangdong color porcelain patterns, and constructing a modeling primitive language of a semantic body;
it should be noted that, semantic analysis is performed on the elements of the wide color porcelain, which may be to perform semantic analysis on the forms, colors, elements and themes of the wide color porcelain, explore and extract semantic connotations and emotional elements of the wide color porcelain, and perform association, divergence and recombination on the semantics after acquiring specific semantics.
In the application, 5 modeling primitive languages are constructed by the expression ontology, specifically: classes, relationships, functions, axioms, and instances. The set of categories is the term and concept related to the field of the colored porcelain, such as classification, process, manufacturing method, etc. The classification of the categories can be divided into primary concepts such as a plate, a dish, a basin, a bowl, a cup, a pot, a cup, a bottle, a painting and the like in a specific embodiment, and the classification under the primary concepts is classified into secondary concepts; the concept represents a set of objects, the relationship pair represents a set of object tuples, and the concept adopts a framework structure and comprises a name of the concept, a set of relationships with other concepts and a description of the concept by semantics.
It should be noted that the relationship includes an object relationship attribute and a value relationship attribute, where the object relationship attribute is used to describe the relationship between classes.
The function is used for describing the relationship between the concept and the data type; axioms (axioms) is a restricted description of classes and attributes in the body of the Guangdong color porcelain; an instance is a representation of an object.
S200, acquiring explicit knowledge and implicit knowledge of the colorful porcelain knowledge according to a knowledge management principle;
it should be noted that explicit knowledge means that explicit knowledge can be expressed in language, text, body, diagram, etc., i.e., knowledge that can be understood by others through expression; implicit knowledge is the knowledge that needs to be further understood through the outer layers. Ontologies also exhibit different hierarchies in describing real-world knowledge. In the application, the library corresponding to the implicit knowledge comprises a knowledge base, wherein the knowledge base comprises semantic ontology knowledge information and corresponding pattern information; the library corresponding to the explicit knowledge comprises a case sample library, and the case sample library comprises images, texts, audios and videos of the colorful porcelain.
It should be noted that, in the present application, the existing relatively stable knowledge resources are described formally by using general knowledge and domain knowledge, and the dynamic knowledge aims at the interactive learning of the knowledge by the user and the fact that dynamically occurs in reality, such as the formal description of the entity object of the wide-color porcelain; secondly, aiming at the current situation that knowledge covers the culture application field, knowledge system construction is carried out on the knowledge in the application field, the field terms and the incidence relation are described formally, and cross-field sharing of the knowledge is realized; and finally, establishing a relation among knowledge of different languages according to the multi-language characteristics of the knowledge, realizing the mapping association of cross-language knowledge, and gradually refining the constructed concept of the multi-dimensional semantic ontology description from abstraction to concrete according to different application ranges. The concept of the general knowledge and the concept of the domain knowledge are mainly expressed as a relatively stable hierarchical structure, and the domain attribute of the concept is increased while the concept of the domain knowledge inherits the attribute of the general concept. The dynamic knowledge mainly describes the fact that the reality dynamically occurs, the knowledge may be directly from the upper general knowledge and the domain knowledge, and the new knowledge connotation is dynamically added according to the characteristics of the application scene, and the dynamic knowledge is mainly expressed as a dynamic network structure.
Step S300, dividing the library corresponding to the explicit knowledge and the implicit knowledge into a general knowledge body, a dynamic knowledge body and a domain knowledge body;
it should be noted that the general ontology includes general concepts: the history, process, color and border of the porcelain with the colorful porcelain. The Guangxi porcelain also can consider selecting universal words in the field of porcelain, and enriches the available vocabulary, thereby constructing a knowledge system of a certain number of universal concepts.
Domain ontology refers to knowledge that describes a particular application domain and discipline. The domain knowledge ontology has strong subject dependence, such as the fields of industry, art and the like. The method is characterized in that the commonly recognized concepts in the field are required to be clarified for constructing the field knowledge, and the concepts and the relation among the concepts are represented by a formalized model, so that the common understanding of the field knowledge is realized. For example, the ceramic belongs to the field of industry, and the manufacturing process of the wide-color porcelain taking the ceramic as the raw material can search a more appropriate concept vocabulary in the industrial term.
The dynamic knowledge body takes the actual requirements of users as traction, the construction process utilizes the existing knowledge and network data resources and is automatically completed by a machine, and the dynamic knowledge body mainly focuses on objects in specific tasks, events or activities and the relation among the objects. For example, in the personalized learning process of the wide-color porcelain, some dynamic knowledge can be selected according to the learning dynamics and the input labels of the user and the information about the wide-color porcelain, so that the construction of the body model of the wide-color porcelain is further assisted. The dynamic knowledge has strong expandability, can continuously track, actively responds to new dynamics, and realizes the dynamic expansion and maintenance of the knowledge.
S400, fusing a general knowledge ontology, a dynamic knowledge ontology and a field knowledge ontology into a colorful porcelain knowledge model;
and S500, constructing a semantic retrieval model for personalized learning based on the Guangdong porcelain knowledge model.
It needs to be explained that a practical and easy-to-use retrieval mode needs to be provided after the Guangdong color porcelain knowledge model is built, the semantic retrieval model is built based on the Guangdong color porcelain knowledge model, the work of a semantic retrieval search engine is no longer restricted by the face of a request sentence input by a user, the real intention behind the sentence input by the user is captured, and the search is carried out according to the real intention, so that a search result which best meets the requirement of the user is more accurately returned to the user. The semantic search fully mines semantic information contained in webpage document information, simultaneously converts retrieval requirements of users into corresponding semantic representations, distinguishes and infers the semantic representations based on the domain ontology, understands user query from semantic level, and returns results inferred based on the ontology to the users. The semantic retrieval and recommendation based on the ontology can help the user to continuously adjust the retrieval vocabulary of the user and change the retrieval strategy so as to obtain the most relevant knowledge, effectively make up for the deficiency of keyword retrieval, and remarkably improve the accuracy of the query result.
The search process of the semantic search model, which may be referred to in fig. 2, includes:
step S510, acquiring a user request, and extracting a semantic label according to the user request;
step S520, performing information reasoning according to the semantic label to perform extended query on the Guangdong porcelain knowledge model;
step S530, the search result is filtered and pushed to the user.
In a specific embodiment, after performing semantic search to obtain a search result, a user may perform personalized learning on the search result and perform a personalized learning process through a semantic search model, with reference to fig. 3, including:
step S531, generating image description according to the semantic retrieval result;
and step S532, extracting and reusing the configuration of the wide color porcelain according to the image description.
The application provides a construction method of a broad-color porcelain knowledge base based on a semantic ontology, which comprises the following steps: performing semantic analysis on the Guangdong porcelain elements according to the Guangdong porcelain patterns, and constructing a modeling primitive language of a semantic ontology; acquiring explicit knowledge and implicit knowledge of the colorful porcelain knowledge according to a knowledge management principle; dividing a library corresponding to the explicit knowledge and the implicit knowledge into a general knowledge ontology, a dynamic knowledge ontology and a domain knowledge ontology; fusing a general knowledge ontology, a dynamic knowledge ontology and a domain knowledge ontology into a colorful porcelain knowledge model; and constructing a semantic retrieval model for personalized learning based on the Guangdong porcelain knowledge model.
This application combines the modeling primitive language of body through the elementary meaning analysis to the wide and colorful porcelain, has constructed the wide and colorful porcelain knowledge model and the semantic retrieval model of multidimension semantic body from the angle that knowledge was used, has strengthened the practicality and the ease for use of wide and colorful porcelain knowledge base, can promote people to the propagation and the study of traditional culture, further provides new way for the study inheritance that people participated in traditional culture.
The terms "first," "second," "third," "fourth," and the like in the description of the present application and in the above-described drawings are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used is interchangeable under appropriate circumstances such that the embodiments of the application described herein are, for example, capable of operation in sequences other than those illustrated or otherwise described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
It should be understood that in the present application, "at least one" means one or more, "a plurality" means two or more. "and/or" for describing an association relationship of associated objects, indicating that there may be three relationships, e.g., "a and/or B" may indicate: only A, only B and both A and B are present, wherein A and B may be singular or plural. The character "/" generally indicates that the former and latter associated objects are in an "or" relationship. "at least one of the following" or similar expressions refer to any combination of these items, including any combination of single item(s) or plural items. For example, at least one (one) of a, b, or c, may represent: a, b, c, "a and b", "a and c", "b and c", or "a and b and c", wherein a, b, c may be single or plural.
The above embodiments are only used for illustrating the technical solutions of the present application, and not for limiting the same; although the present application has been described in detail with reference to the foregoing embodiments, it should be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions in the embodiments of the present application.
Claims (9)
1. A construction method of a broad-color porcelain knowledge base based on semantic ontology is characterized by comprising the following steps:
performing semantic analysis on the Guangdong porcelain elements according to the Guangdong porcelain patterns, and constructing a modeling primitive language of a semantic ontology;
acquiring explicit knowledge and implicit knowledge of the colorful porcelain knowledge according to a knowledge management principle;
dividing the library corresponding to the explicit knowledge and the implicit knowledge into a general knowledge ontology, a dynamic knowledge ontology and a domain knowledge ontology; the library corresponding to the explicit knowledge comprises a case sample library, and the case sample library comprises images, texts, audios and videos of the Guangxi porcelain;
fusing a general knowledge ontology, a dynamic knowledge ontology and a domain knowledge ontology into a colorful porcelain knowledge model; the body of the dynamic knowledge is drawn by the actual requirements of users, the construction process utilizes the prior knowledge and network data resources and is automatically completed by a machine, and the body of the dynamic knowledge mainly focuses on objects and relations among the objects in specific tasks, events or activities;
and constructing a semantic retrieval model for personalized learning based on the Guangdong porcelain knowledge model.
2. The method for constructing a Guangxi porcelain knowledge base according to claim 1, wherein the Guangxi porcelain elements are subjected to semantic analysis, and the Guangxi porcelain elements comprise: the shape, color, elements and theme of the colorful porcelain works.
3. The method for constructing the Guangchong porcelain knowledge base according to claim 1, wherein the modeling primitive language comprises: the method comprises the following steps of (1) classes, relations, functions, axioms and examples, wherein the classes are terms and concepts related to the field of the Guangdong colored porcelain;
the relationship comprises an object relationship attribute and a value relationship attribute;
the function is used for describing the relationship between the concept and the data type;
the instance is a representation of an object.
4. The method for constructing the knowledge base of the Guangxi porcelain according to claim 3, wherein the concepts comprise a primary concept and a secondary concept, the concepts represent a set of objects, the relationship pairs represent a set of object tuples, and the concepts adopt a framework structure and comprise names of the concepts, sets of relationships with other concepts and descriptions of the concepts by semantics.
5. The method for constructing the knowledge base of the wide-color porcelain according to claim 1, wherein the library corresponding to the implicit knowledge comprises a knowledge base, and the knowledge base comprises semantic ontology knowledge information and corresponding pattern information.
6. The method for constructing the knowledge base of the wide-color porcelain according to claim 1, wherein the general knowledge ontology comprises general concepts: the history, process, color and border of the porcelain with the colorful porcelain.
7. The method for constructing a knowledge base of Guangdong porcelain according to claim 1, wherein the domain knowledge ontology refers to knowledge describing a specific application domain and subject.
8. The method for constructing the Guangchong porcelain knowledge base according to claim 1, wherein the search process of the semantic search model comprises the following steps:
acquiring a user request, and extracting a semantic tag according to the user request;
performing information reasoning according to the semantic tags to perform extended query on the Guangdong porcelain knowledge model;
and screening the retrieval result and pushing the retrieval result to the user.
9. The method for constructing the wide-color porcelain knowledge base according to claim 1, wherein the process of performing personalized learning through the semantic retrieval model comprises:
generating image description according to the semantic retrieval result;
and carrying out the configuration extraction and reuse of the wide color porcelain according to the image description.
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