The BA scale-free network evolution model assumes that one node enters at every unit time, which does not adequately reflect team entries that usually occur during the evolution of many practical networks, i.e. the phenomenon of motif embedment. Unfortunately, there are no specific studies on how the motif embedment mechanism affects the degree distribution of networks. In order to solve this problem, an extended scale-free network evolution model with global coupling motif embedment and with the motif size obeying an arbitrary discrete probability distribution (called the MEEBA model for short) is formulated with the help of the ‘motif’ concept. Using the Markov chain method, the accurate analytical expression of the network degree distribution of the MEEBA model is obtained and the correctness of the equation is verified through comparisons with numerical simulation results. The study results show that the right tail of the degree distribution of the MEEBA model still has a power-law behavior, while its left tail reflects the horse-head-like shapes of the degree distribution of many real networks. Furthermore, the power-law exponent and the horse-head shapes are both related to the distribution of the motif size. When the motif size follows a one-point distribution, the network degree distribution of the MEEBA model degenerates into a two-parameter Waring-like distribution and its horse-head shapes disappear. In particular, if the expectation of the one-point distribution is 1, the MEEBA model further degenerates to the BA model. Finally, the practicality and effectiveness of the MEEBA model are verified through a case study.
Abstract.Compared with the traditional domain ontology construction method and the lifecycle thinking of software engineering, the main steps of constructing the domain ontology are to construct purpose, overall design, detailed design, ontology consistency test and ontology evaluation. Using "Thesaurus for Geographic Sciences" as data source and OWL as description language to construct domain ontology, the focus of the process is to determine the concept of the thesaurus, the level of relations between concepts and representations, relationships and so on, realizing conversion of the thesaurus to the domain ontology in the final. By constructing the domain ontology of geographic science, the semantic retrieval based on ontology is realized, solving the problem of traditional information retrieval based on grammatical matching and improving the quality of information retrieval. 1.IntroductionOntology, which originally belonged to the concept of the metaphysics branch of philosophical domain, was described as a systematic description of objective things, which was later introduced into the field of information science, and there is no unified concept. In the early 1990s, the concept of ontology was widely introduced into computers, especially artificial intelligence, knowledge engineering and other fields, as the basis of knowledge expression. Tom Gruber in Stanford University believes that ontology is a clear specification of the conceptual model, while Studer et al.in the University of Karlsruhe optimize the concept of ontology, concluding that ontology is a clear formal specification of shared conceptual models. At the beginning of this century, China began to study ontology in the field of library and information. At the same time, library and information is also an important place for ontology application, and then ontology got a wide range of applications in semantic web, intelligent information retrieval, natural language processing, knowledge management, heterogeneous information integration and so on. Traditional ontology construction is mainly based on manual construction of domain experts or dictionaries, which is time-consuming and low-automatic. Therefore, it is the focus of this paper to construct ontology with efficient methods and steps. 2.Research Status of Ontology Construction Based on ThesauriThe ontology, a visualization of concept, standardized the concept of abstraction in the real world, which makes the relationship between concept and concept, concept and object, concept and object more clear, and reduces the ambiguity to achieve knowledge reuse and sharing purpose. After the introduction of ontology into the field of computer science, many research institutions at home and abroad have carried out research on the related problems of domain ontology construction based on thesauri. At present, a large number of relatively mature ontology have been developed.
Abstract:The traditional library lectures are based on the physical space environment, which is problematic in terms of user needs analysis, time selection, and resource utilization, so that the value of the library unexploited.University library's online lecture system adopts the three-tier architecture design pattern, which based on ASP.NET as the development platform and SQL Server as the back-end database, designing the system to solve the problems in the traditional library service.The design and implementation of the University library's online lecture system broke the traditional library lecture mode, and further optimized the library service concept, improve the quality of service to meet the diverse needs of the user groups. Integrating online test, interactive question and answer, feedback mechanism to the system, the system has a good user experience, visual way to show the audience's learning situation and other information, optimize the content and quality of services to make comments and suggestions.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.