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    Dynamic Knowledge Recommendation Service Model of Online Academic Community Based on Ternary Interactive Determinism
    ZHAO Xueqin, WANG Qingqing, CAI Quan
    Journal of Library and Information Science in Agriculture    2021, 33 (5): 4-13.   DOI: 10.13998/j.cnki.issn1002-1248.20-1054
    Abstract269)      PDF(pc) (1045KB)(165)       Save
    [Purpose/Significance] This paper constructs a dynamic knowledge recommendation service model oriented to online academic communities based on ternary interactive determinism to provide a theoretical basis for online community multi-dimensional demand analysis and demand evolution trend description, to improve the knowledge community recommendation services. [Method/Process] Firstly, based on the ternary interactive determinism, we clarify the internal and external factors that affect the user's knowledge needs and analyze the relationship between the factors. Secondly, according to the needs analysis objective of the ternary interactive determinism, we clarify the corresponding analysis methods and extract the characteristics of users' knowledge needs in various dimensions. Finally, we integrate the demand characteristics of various dimensions and build a knowledge demand chain to describe the evolution of user demand under the interaction of the three elements. We use the similarity of the demand chain to calculate and predict the future knowledge demand of users to expand the analysis of users' knowledge demand. [Results/Conclusions] The knowledge recommendation service system based on the ternary interactive determinism fully considers the various influencing factors of user needs from a global perspective, improves the fine-grained characterization of user needs in the community, and provides reference for academic communities to improve their knowledge service levels.
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    Difference Analysis of Research Topics in a Specific Domain Based on Different Content Levels
    ZHAO Lei, ZHANG Chengzhi
    Journal of Library and Information Science in Agriculture    2021, 33 (5): 14-27.   DOI: 10.13998/j.cnki.issn1002-1248.20-1061
    Abstract207)      PDF(pc) (8707KB)(81)       Save
    [Purpose/Significance] This paper aims to explore whether there are differences in the title and abstract, citation content, and full-text content on research topic, and analyze whether the topic content in the title and abstract can reveal the research content of the full text and the effect of the citation content on the content of the citing literature, so as to provide theoretical support for analyzing the research content of the full text based on the title and abstract of the literature. [Method/Process] This paper conducts an empirical study using Chinese journal papers in the field of COVID-19, extracts feature words from the titles and abstracts, citations and full-text contents of the literature, uses the clustering algorithm to cluster the feature words, and then uses manual interpretation to identify the research topics, and conducts a comparative study to analyze the topic differences among the three parts. [Results/Conclusions] The results show that: the research topics are different in the title and abstract, citation content and full-text content of the literature; compared with the title and abstract, the full text contains more topic content, but the difference in the topic content is small, so the topic content in the title and abstract can be used to represent the research content of the full text; the content of the citation is related to the topic of the citing literature, and they can complement each other.
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    Review on the Application and Development Strategies of Text Mining in Agriculture Knowledge Services
    SUN Tan, DING Pei, HUANG Yongwen, XIAN Guojian
    Journal of Library and Information Science in Agriculture    2021, 33 (1): 4-16.   DOI: 10.13998/j.cnki.issn1002-1248.20-1197
    Abstract357)      PDF(pc) (1625KB)(296)       Save
    [Purpose/Significance] Under the new ecological environment of scientific and technological innovation supporting data-intensive scientific discovery, the new format of knowledge service is quietly taking shape. Text mining as the core of knowledge service is facing challenges under the environment of new knowledge service formats. This paper aims to discuss the development strategies of using text mining to carry out knowledge services in the new environment. [Method/Process]This paper sorts out the technical framework of text mining, and demonstrates that text mining is gradually maturing. Using the research and practice in the field of agriculture as a case study in such areas as information retrieval, intelligent question-answering, information monitoring and knowledge extraction, text mining has shown a good performance in scientific and technological innovation and industrial applications. [Results/Conclusions] This paper puts forward the knowledge service technology development strategies according to China's conditions: (1) constructing a specialized knowledge service system based on text mining technologies, (2) attaching importance to the construction of corpora and basic knowledge bases, and (3) giving priority to implementing the deployment of knowledge service technologies in key areas.
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    Building an Artificial Intelligence Engine Based on Scientific and Technological Literature Knowledge
    ZHANG Zhixiong, LIU Huan, YU Gaihong
    Journal of Library and Information Science in Agriculture    2021, 33 (1): 17-31.   DOI: 10.13998/j.cnki.issn1002-1248.20-0797
    Abstract538)      PDF(pc) (3230KB)(469)       Save
    [Purpose/Significance] How to use the knowledge in the scientific and technological literature to train and improve the model of deep learning algorithm, and acquire knowledge and discover knowledge is an important subject of information research. In order to fully mine and utilize the value of literature knowledge, this paper proposes the goal of building an artificial intelligence (AI) engine based on scientific and technological literature knowledge. [Method/Process] It chooses the literature and information science work as the starting point and takes the scientific and technological literature as the most important carrier of human knowledge. This paper explores the essence of the rapid breakthrough of AI, and innovatively puts forward the construction idea of "science and technology knowledge engine" which is the transformation from "science and technology literature library" in the field of information science. [Results/Conclusions] This paper discusses the construction practice of AI engine based on scientific and technological literature knowledge and explores the method of using the deep learning technology to excavate knowledge to serve information research, so as to provide reference for peers.
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    A Database Construction of S&T Intelligence Cognition Models
    LIU Xiwen, GUO Shijie
    Journal of Library and Information Science in Agriculture    2021, 33 (1): 32-40.   DOI: 10.13998/j.cnki.issn1002-1248.20-0969
    Abstract473)      PDF(pc) (1405KB)(279)       Save
    [Purpose/Significance] This paper aims to study the organization and construction methods of the intelligence cognition models database to help scientists and information analysts to have an accurate understanding of the research area within a short period of time, and assist them in identifying technological opportunities and threats. [Method/Process] The intelligence cognition models database contains various technical elements and literature information across different subjects, so it consists of literature library, algorithm library, scientific/technical knowledge library, application cases library, etc. It has functions including research hotspots identification, technical performance comparison, information analysis methods recommendation, algorithm-aided design and so on. The construction process of the database includes the collection, verification, storage, organization, and utilization of the "intelligence cognitive models", among which the verification of the models is a crucial step. [Results/Conclusions] The intelligence cognition models database is of great significance to the scientific and technological information study and it can play the role of data infrastructures and information analysis toolboxes. The construction of the database requires the cooperation of the information analysts, scientists, and information technology specialists. In the future, the maintenance, application and upgrading of the models library need to be further considered.
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    Diachronic Analysis of Word Frequency in the First Document of Chinese Party Central Committee Based on People's Daily Corpus
    HUANG Shuiqing, Wang Dongbo
    Journal of Library and Information Science in Agriculture    2020, 32 (3): 4-9.   DOI: 10.13998/j.cnki.issn1002-1248.2020.02.17-0073
    Abstract1198)      PDF(pc) (1162KB)(336)       Save
    [Purpose/Significance] The aim of this study is to reveal the characteristics of our times of important words in the No. 1 Central Document, the first document issued by the Central Committee of the Communist Party of China every year. [Method/Process] Taking the People's Daily corpus processed by manual word segmentation as the research object, the frequency of several important words in the No.1 Central Document of 2020 which have appeared in People's Daily corpus in January since 2015 is calculated. From a diachronic perspective, this paper compares the changes of word frequency in People's Daily in different periods and analyzes the reasons. [Results/Conclusions] First, words about macro top-level decision making policies and common social phenomena are found to have higher frequency in People's Daily corpus. Second, words related to three rural issues, i.e. agriculture, rural area and farmers, do not have higher frequency, especially those related to specific jobs. Finally, it is feasible to use People's Daily corpus as a basis to conduct the diachronic analysis of word frequency of policy making documents.
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