Subjects: Library Science，Information Science >> Library Science submitted time 2023-08-26 Cooperative journals: 《图书情报工作》
Abstract： [Purpose/significance] Discovering the interdisciplinary literature is an important prerequisite for interdisciplinary research. Finding domain-related interdisciplinary publications from vast amounts of literature quickly and accurately will help researchers understand the new tendency of interdisciplinarity and identify the focal and hot themes of the field rapidly. This paper presents a novel approach to discover the interdisciplinary literature based on Rao-Stirling diversity indices. Focusing on the case study in the field of nanoscience & nanotechnology, we discussed the feasibility of the method.[Method/process] Based on the nanoscience and nanotechnology publications in the Web of Science, we mapped references to the Web of Science Category, constructed the subject distribution matrix and calculated the interdisciplinary measure indices of the documents based on Python and R to find the interdisciplinary literature.[Result/conclusion] The paper shows that the interdisciplinary literature discovery method based on Rao-Stirling diversity indices can measure the degree of interdisciplinarity in the publication level and discover the interdisciplinary publications in the field of nanoscience and nanotechnology. The method could be applied to other research fields.
Subjects: Library Science，Information Science >> Library Science submitted time 2023-07-26 Cooperative journals: 《图书情报工作》
Abstract： [Purpose/significance] Author-Topic model, as a new probabilistic model which has a high degree of attention in computer science, has been widely applied in text mining, natural language processing and other fields in recent years. This paper analyzes the ideas and applications of AT model and its improved models to grasp its research status and provide reference and ideas for researchers in computer science, library and information science or some other related fields. [Method/process] Using data sets on Web of Science Core Collection, DBLP and CNKI (China Academic Journals Full-text Database), a literature collection on Author-Topic model and its improved models is constructed through the establishment of retrieval rules, data de-duplication, artificial judgment and other operations. This paper summarizes the existing research based on literature analysis method from the perspective of the application process of the model. [Result/conclusion] The results show that the existing related research has formed a comparatively complete analysis process and the improvement angle and application area of the models are increasingly diversified. However, some problems, such as performance optimization, standardization and perfection and further application in the field of library and information science, still need to be explored in depth.
Subjects: Library Science，Information Science >> Information Science submitted time 2023-04-01 Cooperative journals: 《图书情报工作》
Abstract： [Purpose/significance] The identification results of the LDA model is sometimes unsatisfactory due to some meaningless topics mixed together. Therefore, it's quite necessary to establish an effective topic filtering method to eliminate these noise topics and to ensure the accuracy of subsequent evolution analysis.[Method/process] Based on the co-occurrence relationship between keywords, keywords relevance index (KRI) was constructed. Taking the field of single cell research as an example, KRI values of the distribution of theme-keywords were calculated and compared with the results of manual interpretation.[Result/conclusion] Experimental results show that this method can effectively eliminate meaningless noise topics in the LDA model recognition results, which can improve the accuracy of topic recognition and the subsequent topic evolution analysis. It also helps to reduce the dependence on manual interpretation in the process of topic identification through the topic model method.
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