Research On The Search And Absorption Of Literature Knowledge Based On The Principle Of Snowball

The essence of innovation is knowledge production.As an important carrier of knowledge,literature is a medium for users to acquire knowledge quickly and is a precondition for conducting scientific research.At the same time,literature plays an irreplaceable role in knowledge exchange and dissemination and information acquisition.Therefore,it is very important to search and absorb the knowledge in the literature.Relevance is a key factor in the search of documents,and it is the core research content in the field of information science and information retrieval.This paper studies the effect of the presentation results of search results on the relationship between document knowledge and knowledge derivation,and the relevance of users' judgment on literature.The major innovations of the paper are as follows:(1)The model of document retrieval results is presented at the network level based on snowballing principles.At present,the results presentation methods on the literature retrieval platform are all arranged sequentially.This presentation method obscures the logical relationship between documents,leads to the fragmentation of knowledge and hinders the formation of cognitive ability,and because the relationship between the knowledge in the literature cannot be visualized The emergence of information led to the lack of information,is not conducive to the user to absorb and reuse the knowledge in the literature.Based on past research,this paper studies the search and absorption of knowledge in the literature.A theoretical model based on snowball theory for presenting literature retrieval results at the network level is designed.From the perspective of network relations,the relationship between knowledge and knowledge in the literature is intuitively presented in a hierarchical manner in the form of networks,avoiding failure to visualize The lack of information caused by the connection between the literature and the knowledge facilitates the user's absorption and utilization of the knowledge in the literature and improves the efficiency of the search and absorption of the literature knowledge.(2)A hierarchical network presentation model based on comprehensive relevance judgment.With regard to the influence of document retrieval presentation methods on user relevance judgment,previous scholars mainly studied the influence of sequential presentation methods on user relevance judgments,and sequential presentations made it easy for users to judge the relevance of documents when they were related to "order effects".Due to the"and first reason" effect,and the order of the current order is mainly based on the topic related,published time,downloads and cited relationships to sort,without a comprehensive consideration of a number of factors,it will have a negative impact on users to obtain relevant knowledge.Therefore,based on the literature retrieval results model presented at the network level,considering the excessive correlation of literature knowledge in the network may cause information redundancy,this paper makes further optimization and improvement from the perspective of relevance.The introduction of the calculation of the comprehensive correlation degree,by calculating the comprehensive correlation of the nodes in the network,eliminating the nodes with lower correlation in the network,thereby improving the overall relevance of the network,and avoiding the redundancy of information in the network,facilitating the user The relevance judgment of the literature knowledge further improves the user's search and absorption efficiency of the relevant knowledge in the literature,thereby improving the user's satisfaction.In order to verify the validity and feasibility of the model,this article selected 30 scholars as the data source for the analysis of the examples of the model,and by investigating the experimental application of scientific research personnel,confirmed that the model can help users quickly Absorb knowledge,improve knowledge search and absorption efficiency.This proves the effectiveness and feasibility of this model.