Subjects: Library Science，Information Science >> Library Science submitted time 2023-10-08 Cooperative journals: 《知识管理论坛》
Abstract： [Purpose/Significance] In the context of deep digital development, digital humanities as a development field of interdisciplinary deep integration, the scientific research cooperation among scholars is becoming more and more frequent. It is necessary to analyze and excavate the increasingly complex cooperation relationship, to help scholars obtain potential cooperation opportunities to promote academic exchanges. [Method/Process] In this paper, scholars, institutions and keywords were used as node data, and coauthors, citations, posts and research topics were used as relational data to build scholar-collaboration graphs, which was stored based on the graph database Neo4j. Cypher query language and GDS algorithm library were used to analyze the cooperation community discovery, core scholar identification and cooperation trend prediction of scholars in the field of digital humanities. [Results/Conclusion] The experimental results show that Neo4j can better realize the construction and analysis of scholars’ cooperation network in the field of digital humanities. It can help scholars quickly find interdisciplinary scholars who are highly related to their research interests and directions among many researchers, so as to promote scholars’ cooperation and discipline development in the field of digital humanities.
Subjects: Library Science，Information Science >> Information Science submitted time 2023-04-01 Cooperative journals: 《图书情报工作》
Abstract： [Purpose/significance] Aiming at the application of sequence alignment algorithm in text similarity, the global alignment algorithm is improved and the accuracy of the algorithm is improved. At the same time, the local alignment algorithm is used to effectively solve the problem of comparing two texts with different content or with different length. [Method/process] First, the CRF model in HanLP was used to normalize the Chinese text data set of the online academic resources and constitute the Chinese sequence set. Then, Word2Vec model was trained with the latest Chinese Wikipedia corpus to construct the word pair scoring matrix. Finally, based on the scoring matrix and the improved scoring rules, the two Chinese sequences of global/local alignment were compared and the optimal solution of the alignment was obtained. The optimal solution was backtracked to obtain the alignment path of the optimal solution and the similarity of the two Chinese sequences was calculated. [Result/conclusion] The experiment results show that compared with the current research of global alignment algorithm, the method based on the results of the part-of-speech tagging and Word2Vec build words to further improve the global alignment score matrix algorithm and applied to the accuracy of computing text similarity of local alignment algorithm can effectively solve the content differences or differences in the length of two text comparing problems.
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