# Cloud Computing-Based Online Sharing Method of Mass Resources in Public Libraries

Authors: Jun Cao
Journal: Mobile Information Systems
 (2022)

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## Abstract

In order to realize the online sharing of massive resources and capitals in public libraries under the circumstances of network environment and cultural construction, it is desirable to invent new sharing policies. In this paper, we put forward a method of online sharing of massive resources in public libraries which is established on cloud computing. Cloud computing technique is implemented to collect the statistical information characteristics of public library’s massive resources under the condition of network environment and culture construction, and an adaptive fusion clustering processing model of public library’s massive resources under the condition of network environment and culture construction is constructed. Moreover, the correlation statistical feature detection approach is used to accomplish fuzzy scheduling and feature mining of public library’s massive resources under the condition of network environment and culture construction. The information storage center management database of public library’s massive resources under the condition of network environment and culture construction is established. The fuzzyC-means clustering approach is implemented in the database to cluster the massive resources of public library under the condition of network environment and culture construction. Combined with cloud computing technology, the sharing and classified management scheduling of massive resources of public library under the condition of network environment and culture construction are comprehended. The simulation outcomes confirm that the adaptive performance of public library’s massive resource sharing management under the condition of network environment and culture construction is better, and the adaptive scheduling performance of resources is better. The data clustering of public library’s massive resources under the condition of network environment and culture construction is stronger, which improves the online sharing level of public library’s massive resources under the condition of network environment and culture construction.


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## Body

## 1. Introduction

The public library’s information service, resource construction, and other projects should not stagnate at the traditional level but should be increasingly integrated and comprehensive with the development of the times. As modern society belongs to the era of knowledge economy explosion, people’s demand for social information is increasing. At present, library resources cannot reasonably meet the public’s demand for cultural information, but it is unrealistic for libraries to expand their scale [1]. Combining the national conditions and foreign practical experience, we should make effective use of Internet resources, so that the public can enjoy equal rights to use resources. The total resources of public libraries are huge, and they can be equipped with relevant literature retrieval technology, which is the advantage that other social libraries do not have in terms of professionals, technical equipment, etc., and can provide new resource power for the development of local social economy and culture. University libraries should serve public utilities, improve citizens’ quality, and promote social progress. Obviously, it is far from enough for a library to rely solely on its own collection resources, and “closing the country to the outside world” only brings backwardness. Modern era is an era of knowledge economy and sharing economy. Sharing economy is popular in recent years. Sharing economy takes the platform created by a third party as its primary feature and digital information technology as its foundation. Nowadays, we can see bike-sharing and shared charging treasures everywhere, which not only bring benefits to businesses but also bring benefits to society. Obviously, in the field of information, if we want to realize the maximum utility of information and achieve the purpose of informationization, we must constantly share resources [2, 3].With the development of public library’s massive resource management technology under the condition of intelligent network environment and culture construction, the intelligent information management system is adopted to classify, manage, and share public library’s massive resources under the condition of network environment and culture construction, to improve the utilization efficiency of public library’s massive resources under the condition of network environment and culture construction, and to carry out the optimal design of public library’s massive resource management under the condition of network environment and culture construction under the cloud computing environment [4]. This paper extracts the big data distribution features of public library’s massive resources under the condition of network environment and culture construction and combines the methods of correlation feature information detection and fuzzy cluster analysis to design the management and sharing of public library’s massive resources under the condition of network environment and culture construction, so as to promote the upgrading of public library’s massive resources information management level under the condition of network environment and culture construction [5]. In fact, it is of utmost importance to study the sharing technology of mass possessions in public libraries under the condition of network environment and cultural construction. Under the condition of network culture construction, the massive resources of public libraries refer to the construction of a unified platform for all university libraries, the mutual assistance of resources in all libraries, the mutual cooperation and coordination of resources, the use of different technologies and methods, the assistance and utilization of information resources among all libraries, and the joint construction of information resources when cooperating with each other, so as to meet the readers’ demand for comprehensive information resources activities to the greatest extent [6, 7].On the basis of intelligent information processing and integrated scheduling of public library’s massive resources under the condition of network environment and culture construction, the method of cloud integration and adaptive scheduling of public library’s massive resources under the condition of network environment and culture construction is studied, and the fuzzy association rule set of public library’s massive resources under the condition of network environment and culture construction is extracted to realize the optimal management of public library’s massive resources under the condition of network environment and culture construction [8]. This paper constructs an adaptive fusion clustering processing model of public library’s massive resources under the condition of network environment and culture construction, adopts correlation statistical feature detection method to carry out fuzzy scheduling and feature mining of public library’s massive resources under the condition of network environment and culture construction, establishes the information storage center management database of public library’s massive resources under the condition of network environment and culture construction, and realizes the sharing design of public library’s massive resources under the condition of network environment and culture construction. Finally, it makes an experimental analysis and draws an effective conclusion. The key contributions are summarized as follows:(i)
We put forward a method of online sharing of massive resources in public libraries which is established on cloud computing and implemented to collect the statistical information characteristics of public library’s massive resources under the condition of network environment and culture construction.(ii)
An adaptive fusion clustering processing model of public library’s massive resources under the condition of network environment and culture construction is constructed.(iii)
The correlation statistical feature detection approach is used to accomplish fuzzy scheduling and feature mining of public library’s massive resources under the condition of network environment and culture construction.(iv)
The fuzzyC-means clustering approach is implemented in the database to cluster the massive resources of public library under the condition of network environment and culture construction. Combined with cloud computing technology, the sharing and classified management scheduling of massive resources of public library under the condition of network environment and culture construction are comprehended.The remaining sections of the paper are organized in the following manner. The distribution and big data analysis of scheduling nodes for sharing mass resources in public libraries are deliberated in Section2. In Section 3, we discuss the mass resource sharing optimization of public libraries. The suggested model is also presented in this section. Simulation tests and results are given in Section 4. The major conclusions are drawn in Section 5 along with some discussion over the extensions of this work.


## 2. Distribution and Big Data Analysis of Scheduling Nodes for Sharing Mass Resources in Public Libraries

### 2.1. Distribution of Scheduling Nodes for Mass Resource Sharing in Public Libraries under the Condition of Network Environment and Cultural Construction

In order to comprehend and understand the intelligent sharing and optimal management and scheduling of public library’s massive resources under the condition of network environment and culture construction within the context of big data and cloud computing, it is indispensable to construct the storage structure model of public library’s massive resources database under the condition of network environment and culture construction and adopt the directed graph analysis method to design the distribution of public library’s massive resource sharing and scheduling nodes under the condition of network environment and culture construction [9]. Assume that the attribute set of the shared scheduling node graph model of public library's massive resource base under the network environment and cultural construction is [s], and use the decision tree and directed graph analysis model to split the binary tree of public library's massive data under the network environment and cultural construction, so that we can get different attribute sets and the distributed storage structure model of public library’s massive resources under the condition of network environment and culture construction is shown in Figure 1. In Figure 1, the distribution pattern of public library’s massive resource sharing scheduling chart under the condition of network environment and culture construction consists of nodes and edges [10–12]. Through principal component analysis and modeling method, a hierarchical adaptive hierarchical planning model of public library’s massive resources under the condition of network environment and culture construction is formed, and the dataset classification and information fusion of public library’s massive resources under the condition of network environment and culture construction are carried out in combination with statistical feature distribution.Figure 1
Distribution model of shared scheduling nodes of public libraries under the condition of network environment and cultural construction.Let us assume that the primitive vector of the useful data test set in the massive resources of public libraries under the condition of network environment and cultural construction is expressed mathematically as follows:(1)Ei,j=e1,e2,⋯,em,where ei∈1,0 is the main feature of the spatial planning dataset of public library’s massive resources under the condition of network environment and culture construction, and four tuples are used to represent the main feature decision tree of public library’s massive resource sharing scheduling under the condition of network environment and culture construction. Ei,Ej,d,t are entities (i.e., nodes and sums) of public library’s massive resources in the directed graph under the condition of network environment and culture construction, Si,jt is the subspace clustering distribution of public library’s massive resources under the condition of network environment and culture construction, and Ti,jt is the information exchange time of file sharing scheduling. In order to reduce the time of public library’s massive resource sharing and scheduling under the condition of network environment and culture construction [13, 14], it is necessary to model the main characteristics of public library’s massive resource distribution under the condition of network environment and culture construction and define the graph model attribute set of public library’s massive resource sharing and scheduling nodes under the condition of network environment and culture construction, where d represents the ontology object of public library’s massive resource distribution under the condition of network environment and culture construction, and p represents the ontology distribution concept related set of public library’s massive resource sharing under the condition of network environment and culture construction. The calculation expression is as follows:(2)Ti,jt=pi,jt−Δptpi,jt.The decision similarity (correlation) of public library’s massive resources under the condition of network environment and cultural construction is expressed byUi,jt. The following feature vector sets are used to analyze the autocorrelation feature quantity of public library’s massive resource sharing under the condition of network environment and cultural construction, which is described as [15](3)V=viji=1,2,⋯,c,j=1,2,⋯,s,where Vi is the correlation analysis measurement value of massive resources of public libraries under the condition of network environment and cultural construction, and the calculation formula is illustrated in the following equation:(4)Ui,jt=exp−bzit−zjt2.Therefore, the similarity measurement factor between the scheduling nodes of mass resource sharing in public libraries under the condition of network environment and cultural construction is modeled as(5)Si,jt=pi,jt−spi,jtpi,jt,where pi,jt is the probability of cross-distribution of useful features in public library’s massive resources at all times under the condition of network environment and cultural construction; Δpt is the relevant weight of massive resources of public libraries under the condition of network environment and cultural construction; spi,jt is the fuzzy decision increment value of the scheduling node of public library’s massive resource sharing under the condition of network environment and cultural construction; and zit, zjt are, respectively, expressed as the distribution weight coefficients of mass resource sharing scheduling nodes of public libraries under the condition of network environment and cultural construction. Conferring to the aforementioned examination and discussion, the data collection and cluster investigation of public library’s massive resource sharing scheduling under the condition of network environment and cultural construction are realized [16].


### 2.2. Big Data Analysis of Massive Resources of Public Libraries under the Condition of Network Environment and Cultural Construction

The linear mapping approach is implemented to build the balanced control model of public library’s massive resources under the condition of network environment and culture construction. Under the condition of double fusion decision [17, 18], the fuzzy decision function of public library’s massive resource sharing big data distribution under the condition of network environment and culture construction is as follows:(6)xt=Reante−j2πfcτntslt−τnt.Assuming that there areP sampling channels for public library’s massive resource sharing big data under the condition of network environment and culture construction, the relevance decision function of public library’s massive resource distribution under the condition of network environment and culture construction is as follows:(7)s¯,a¯=φ2s1,a1,ω1,a1′,s2,a2,ω2,a2′,...,sn,an,ωn,an′=Δ∑j=1nΔ−1ωj,aj′Δ−1sj,aj∑j=1nΔ−1ωj,aj′=Δ∑j=1nβjβj′∑jnβj′,where ∑j=1nωj=1,s¯∈S,a¯∈−0.5,0.5. Therefore, the sharing scheduling problem of distributed data in public libraries under the condition of network environment and culture construction is transformed into a decision-making problem with binary semantics. Assume that the semantic indicator set of massive resource allocation of public libraries under the network environment and cultural construction is [TF], the graph model of public libraries’ massive resources information cross scheduling under the condition of network environment and culture construction is Ek∈Ek=1,2,…,t, and the endogenous fusion scheduling method is adopted. Mining the association rules of public library’s massive resources information under the condition of network environment and culture construction, when the condition Pi∈Pi=1,2,…,m is satisfied, then the corresponding fuzzy evaluation value of public library’s massive resource sharing scheduling under the condition of network environment and culture construction meets the criteria rijk∈S, and then extracting the semantic association and regular feature set of public library’s massive resources under the condition of network environment and culture construction is possible through the method as follows:(8)TFt,ci=Pt|ci∑j⟶nPtj|ci,where T is the statistical characteristic quantity of public library’s massive resource data currently accessed under the condition of network environment and culture construction and ci is the ith category of public library’s massive resources classification attribute set under the condition of network environment and culture construction. Furthermore, j is the jth category attribute set in public library’s massive resources database under the condition of network environment and culture construction, and n is the total number of data classification in public library’s massive resources under the condition of network environment and culture construction. Using the cross-compilation control method, the mass resources of public libraries are shared and scheduled under the condition of network environment and cultural construction, and the difference fusion feature quantity is obtained through the following equation:(9)JmU,V=∑k=1n∑i=1cμikmdik2,where m is the limited dataset index of public library’s massive resource decision-making variable under the condition of network environment and culture construction, and the variable dik2 is the related variable of public library’s massive resource distribution under the condition of network environment and culture construction. This should be noted that the variable SD indicates that the decision-making independent variable of public library’s massive resources under the condition of network environment and culture construction is given by (10) and (11) [18]:(10)dik2=xk−Vi2,and(11)∑i=1cμik=1,k=1,2,⋯,n.Therefore, a big data analysis model of public library’s massive resources under the condition of network environment and culture construction is constructed and established. Moreover, through combining the cloud computing and big data environment, the public library’s massive resource sharing and remarkable characteristics analysis are accomplished. Furthermore, conferring to the positive correlation characteristics analysis method, the resource sharing scheduling is carried out [19].


## 2.1. Distribution of Scheduling Nodes for Mass Resource Sharing in Public Libraries under the Condition of Network Environment and Cultural Construction

In order to comprehend and understand the intelligent sharing and optimal management and scheduling of public library’s massive resources under the condition of network environment and culture construction within the context of big data and cloud computing, it is indispensable to construct the storage structure model of public library’s massive resources database under the condition of network environment and culture construction and adopt the directed graph analysis method to design the distribution of public library’s massive resource sharing and scheduling nodes under the condition of network environment and culture construction [9]. Assume that the attribute set of the shared scheduling node graph model of public library's massive resource base under the network environment and cultural construction is [s], and use the decision tree and directed graph analysis model to split the binary tree of public library's massive data under the network environment and cultural construction, so that we can get different attribute sets and the distributed storage structure model of public library’s massive resources under the condition of network environment and culture construction is shown in Figure 1. In Figure 1, the distribution pattern of public library’s massive resource sharing scheduling chart under the condition of network environment and culture construction consists of nodes and edges [10–12]. Through principal component analysis and modeling method, a hierarchical adaptive hierarchical planning model of public library’s massive resources under the condition of network environment and culture construction is formed, and the dataset classification and information fusion of public library’s massive resources under the condition of network environment and culture construction are carried out in combination with statistical feature distribution.Figure 1
Distribution model of shared scheduling nodes of public libraries under the condition of network environment and cultural construction.Let us assume that the primitive vector of the useful data test set in the massive resources of public libraries under the condition of network environment and cultural construction is expressed mathematically as follows:(1)Ei,j=e1,e2,⋯,em,where ei∈1,0 is the main feature of the spatial planning dataset of public library’s massive resources under the condition of network environment and culture construction, and four tuples are used to represent the main feature decision tree of public library’s massive resource sharing scheduling under the condition of network environment and culture construction. Ei,Ej,d,t are entities (i.e., nodes and sums) of public library’s massive resources in the directed graph under the condition of network environment and culture construction, Si,jt is the subspace clustering distribution of public library’s massive resources under the condition of network environment and culture construction, and Ti,jt is the information exchange time of file sharing scheduling. In order to reduce the time of public library’s massive resource sharing and scheduling under the condition of network environment and culture construction [13, 14], it is necessary to model the main characteristics of public library’s massive resource distribution under the condition of network environment and culture construction and define the graph model attribute set of public library’s massive resource sharing and scheduling nodes under the condition of network environment and culture construction, where d represents the ontology object of public library’s massive resource distribution under the condition of network environment and culture construction, and p represents the ontology distribution concept related set of public library’s massive resource sharing under the condition of network environment and culture construction. The calculation expression is as follows:(2)Ti,jt=pi,jt−Δptpi,jt.The decision similarity (correlation) of public library’s massive resources under the condition of network environment and cultural construction is expressed byUi,jt. The following feature vector sets are used to analyze the autocorrelation feature quantity of public library’s massive resource sharing under the condition of network environment and cultural construction, which is described as [15](3)V=viji=1,2,⋯,c,j=1,2,⋯,s,where Vi is the correlation analysis measurement value of massive resources of public libraries under the condition of network environment and cultural construction, and the calculation formula is illustrated in the following equation:(4)Ui,jt=exp−bzit−zjt2.Therefore, the similarity measurement factor between the scheduling nodes of mass resource sharing in public libraries under the condition of network environment and cultural construction is modeled as(5)Si,jt=pi,jt−spi,jtpi,jt,where pi,jt is the probability of cross-distribution of useful features in public library’s massive resources at all times under the condition of network environment and cultural construction; Δpt is the relevant weight of massive resources of public libraries under the condition of network environment and cultural construction; spi,jt is the fuzzy decision increment value of the scheduling node of public library’s massive resource sharing under the condition of network environment and cultural construction; and zit, zjt are, respectively, expressed as the distribution weight coefficients of mass resource sharing scheduling nodes of public libraries under the condition of network environment and cultural construction. Conferring to the aforementioned examination and discussion, the data collection and cluster investigation of public library’s massive resource sharing scheduling under the condition of network environment and cultural construction are realized [16].


## 2.2. Big Data Analysis of Massive Resources of Public Libraries under the Condition of Network Environment and Cultural Construction

The linear mapping approach is implemented to build the balanced control model of public library’s massive resources under the condition of network environment and culture construction. Under the condition of double fusion decision [17, 18], the fuzzy decision function of public library’s massive resource sharing big data distribution under the condition of network environment and culture construction is as follows:(6)xt=Reante−j2πfcτntslt−τnt.Assuming that there areP sampling channels for public library’s massive resource sharing big data under the condition of network environment and culture construction, the relevance decision function of public library’s massive resource distribution under the condition of network environment and culture construction is as follows:(7)s¯,a¯=φ2s1,a1,ω1,a1′,s2,a2,ω2,a2′,...,sn,an,ωn,an′=Δ∑j=1nΔ−1ωj,aj′Δ−1sj,aj∑j=1nΔ−1ωj,aj′=Δ∑j=1nβjβj′∑jnβj′,where ∑j=1nωj=1,s¯∈S,a¯∈−0.5,0.5. Therefore, the sharing scheduling problem of distributed data in public libraries under the condition of network environment and culture construction is transformed into a decision-making problem with binary semantics. Assume that the semantic indicator set of massive resource allocation of public libraries under the network environment and cultural construction is [TF], the graph model of public libraries’ massive resources information cross scheduling under the condition of network environment and culture construction is Ek∈Ek=1,2,…,t, and the endogenous fusion scheduling method is adopted. Mining the association rules of public library’s massive resources information under the condition of network environment and culture construction, when the condition Pi∈Pi=1,2,…,m is satisfied, then the corresponding fuzzy evaluation value of public library’s massive resource sharing scheduling under the condition of network environment and culture construction meets the criteria rijk∈S, and then extracting the semantic association and regular feature set of public library’s massive resources under the condition of network environment and culture construction is possible through the method as follows:(8)TFt,ci=Pt|ci∑j⟶nPtj|ci,where T is the statistical characteristic quantity of public library’s massive resource data currently accessed under the condition of network environment and culture construction and ci is the ith category of public library’s massive resources classification attribute set under the condition of network environment and culture construction. Furthermore, j is the jth category attribute set in public library’s massive resources database under the condition of network environment and culture construction, and n is the total number of data classification in public library’s massive resources under the condition of network environment and culture construction. Using the cross-compilation control method, the mass resources of public libraries are shared and scheduled under the condition of network environment and cultural construction, and the difference fusion feature quantity is obtained through the following equation:(9)JmU,V=∑k=1n∑i=1cμikmdik2,where m is the limited dataset index of public library’s massive resource decision-making variable under the condition of network environment and culture construction, and the variable dik2 is the related variable of public library’s massive resource distribution under the condition of network environment and culture construction. This should be noted that the variable SD indicates that the decision-making independent variable of public library’s massive resources under the condition of network environment and culture construction is given by (10) and (11) [18]:(10)dik2=xk−Vi2,and(11)∑i=1cμik=1,k=1,2,⋯,n.Therefore, a big data analysis model of public library’s massive resources under the condition of network environment and culture construction is constructed and established. Moreover, through combining the cloud computing and big data environment, the public library’s massive resource sharing and remarkable characteristics analysis are accomplished. Furthermore, conferring to the positive correlation characteristics analysis method, the resource sharing scheduling is carried out [19].


## 3. Mass Resource Sharing Optimization of Public Libraries

### 3.1. Self-Adaptive Fusion Clustering Processing of Massive Resources of Public Libraries under the Condition of Network Culture Construction

On the basis of extracting the statistical information features of public library’s massive resources under the condition of network environment and culture construction by cloud computing, this paper designs the sharing of public library’s massive resources under the condition of network environment and culture construction. In particular, the aim of the work is to put forward the sharing method of public library’s massive resources under the condition of network environment and culture construction based on cloud computing technology. The anticipated approach, in fact, adopts the correlation statistical feature detection method to carry out fuzzy scheduling and feature mining of public library’s massive resources under the condition of network environment and culture construction [20]. This should be noted that the suggested approach obtains the multiple regression constraint expression of adaptive fusion clustering of public library’s massive resources under the condition of network environment and culture construction using equations (12) and (13), respectively:(12)μik=1∑j=1cdik/djk2/m−1,(13)Vi=∑k=1mμikmxk∑k=1nμikm.According to the above constraint parameter index system construction, the statistical information features of public library’s massive resources under the condition of network environment and culture construction are extracted by cloud computing method, assuming that the total number of categories of public library’s massive resources under the condition of network environment and culture construction isM, and the mutual information feature quantity is used to express the concentration of public library’s massive resource data T in ci category under the condition of network environment and culture construction, which is given in the following equation:(14)CONt,ci=logPd|t,ciPd|t=logPd|t,ci∑i⟶mPd|t,ci,where Pd|t,ci is the distribution probability of public library’s massive resource sharing scheduling under the condition of ci network environment and culture construction. In the statistical feature distribution model, the vector set of public library’s massive resource distribution under the condition of network environment and culture construction is not = {xf1, xf2, …, xfr} T. In the next stage, we explicitly express the statistical feature vector of the storage area di of public library’s massive resources under the condition of network environment and culture construction, in fact, combine the fuzzy association rule scheduling method to match the autocorrelation features of public library’s massive resources under the condition of network environment and culture construction, and get the feature matching model as follows:(15)ldij⟶cx=∑v=0cxcosinij⟶xdij,dxvcx−1,where cosinij⟶xdij,dxv is the fusion clustering feature set of public library’s massive resources under the condition of network environment and cultural construction. Note that the well-known sigmoid function is used to normalize the feature mapping formula of public library’s massive resources under the condition of network environment and cultural construction using the following relationship [21]:(16)si=sigmoidMdi=11+e−aMdi+b.At this time, the correlation data vector di of public library’s massive resources under the condition of network environment culture construction is adaptively optimized by fuzzy correlation constraint matrixM, and the shared scheduling set and the directional distribution vector set Si of public library’s massive resources under the condition of network environment culture construction are obtained, where A and B are adjustable coefficients. Suppose that the fuzzy center vector of adaptive fusion clustering of massive resources of public libraries under the condition of network environment and culture construction is vi, and vi=w1,t1,w2,t2,⋯,wj,tj. According to the directional factors of readers of public libraries’ massive resources under the condition of network environment and culture construction, the judgment criteria of public libraries’ massive resource sharing scheduling under the condition of network environment and culture construction are determined as follows:(17)Si,j=∑u∈UijVu,i−3Vu,j−3∑u∈UijVu,i−V.i¯2∑u∈UijVu,j−V.j¯)2,where the priority clustering model of mass resource sharing scheduling data of public libraries under the condition of network environment and cultural construction is given as illustrated in the following mathematical model:(18)Vu,i=Di−Di++Di−,V.j¯=Ri+Ri++Ri−.To sum up, an adaptive fusion clustering processing model of public library’s massive resources under the condition of network environment and culture construction is constructed, and the fuzzy scheduling and feature mining of public library’s massive resources under the condition of network environment and culture construction are accomplished through implementing the correlation statistical feature detection technique [22, 23], so as to improve the sharing level of public library’s massive resources under the condition of network environment and culture construction [24].


### 3.2. Sharing and Scheduling of Mass Resources in Public Libraries

Under the constraint of association rules, cloud computing is adopted to obtain the association rule distribution parameter setY and fuzzy C-means clustering center vector of public library’s massive resource information under the condition of network environment and cultural construction. Thus, obtaining the similarity distribution mapping function of public library’s massive resource information under the condition of network environment and cultural construction under cloud computing is computed using the following equation:(19)SimX,Y=CosX,Y=CX⋅CYCX⋅CY.The information storage center management database of public library’s massive resources under the condition of network environment and culture construction is established, and the fuzzyC-means clustering scheme and procedure are implemented in the database to cluster the massive resources of public library under the condition of network environment and culture construction, and the adaptive updating formula of public library’s massive resource sharing scheduling under the condition of network environment and culture construction is obtained as follows:(20)Rdit−1=minRs,maxRdit+βnt−Nit,(21)Nit=j:xjt−xit<Rdi;lit<ljt.where xjt represents the distribution position of public library’s massive resource sharing big data prior data in the h sensor node of the t generation under the condition of network environment and culture construction. In the same way, the variable ljt represents the mutual information feature quantity of the first sensor node of the generation. Combined with the fuzzy decision classification model, the adaptive scheduling of public library’s massive resource sharing under the condition of network environment and culture construction is carried out, and the scheduling formula is as follows:(22)xit=xit−1+sxjt−1−xit−1xjt−1−xit−1.The autoregressive moving average model is adopted to design the distributed database of public library’s massive resource sharing under the condition of network environment and culture construction, and the probability confidence interval and rejection interval are constructed. Combined with the cloud computing technology, the sharing and classified management scheduling of public library’s massive resources under the condition of network environment and culture construction are realized.


## 3.1. Self-Adaptive Fusion Clustering Processing of Massive Resources of Public Libraries under the Condition of Network Culture Construction

On the basis of extracting the statistical information features of public library’s massive resources under the condition of network environment and culture construction by cloud computing, this paper designs the sharing of public library’s massive resources under the condition of network environment and culture construction. In particular, the aim of the work is to put forward the sharing method of public library’s massive resources under the condition of network environment and culture construction based on cloud computing technology. The anticipated approach, in fact, adopts the correlation statistical feature detection method to carry out fuzzy scheduling and feature mining of public library’s massive resources under the condition of network environment and culture construction [20]. This should be noted that the suggested approach obtains the multiple regression constraint expression of adaptive fusion clustering of public library’s massive resources under the condition of network environment and culture construction using equations (12) and (13), respectively:(12)μik=1∑j=1cdik/djk2/m−1,(13)Vi=∑k=1mμikmxk∑k=1nμikm.According to the above constraint parameter index system construction, the statistical information features of public library’s massive resources under the condition of network environment and culture construction are extracted by cloud computing method, assuming that the total number of categories of public library’s massive resources under the condition of network environment and culture construction isM, and the mutual information feature quantity is used to express the concentration of public library’s massive resource data T in ci category under the condition of network environment and culture construction, which is given in the following equation:(14)CONt,ci=logPd|t,ciPd|t=logPd|t,ci∑i⟶mPd|t,ci,where Pd|t,ci is the distribution probability of public library’s massive resource sharing scheduling under the condition of ci network environment and culture construction. In the statistical feature distribution model, the vector set of public library’s massive resource distribution under the condition of network environment and culture construction is not = {xf1, xf2, …, xfr} T. In the next stage, we explicitly express the statistical feature vector of the storage area di of public library’s massive resources under the condition of network environment and culture construction, in fact, combine the fuzzy association rule scheduling method to match the autocorrelation features of public library’s massive resources under the condition of network environment and culture construction, and get the feature matching model as follows:(15)ldij⟶cx=∑v=0cxcosinij⟶xdij,dxvcx−1,where cosinij⟶xdij,dxv is the fusion clustering feature set of public library’s massive resources under the condition of network environment and cultural construction. Note that the well-known sigmoid function is used to normalize the feature mapping formula of public library’s massive resources under the condition of network environment and cultural construction using the following relationship [21]:(16)si=sigmoidMdi=11+e−aMdi+b.At this time, the correlation data vector di of public library’s massive resources under the condition of network environment culture construction is adaptively optimized by fuzzy correlation constraint matrixM, and the shared scheduling set and the directional distribution vector set Si of public library’s massive resources under the condition of network environment culture construction are obtained, where A and B are adjustable coefficients. Suppose that the fuzzy center vector of adaptive fusion clustering of massive resources of public libraries under the condition of network environment and culture construction is vi, and vi=w1,t1,w2,t2,⋯,wj,tj. According to the directional factors of readers of public libraries’ massive resources under the condition of network environment and culture construction, the judgment criteria of public libraries’ massive resource sharing scheduling under the condition of network environment and culture construction are determined as follows:(17)Si,j=∑u∈UijVu,i−3Vu,j−3∑u∈UijVu,i−V.i¯2∑u∈UijVu,j−V.j¯)2,where the priority clustering model of mass resource sharing scheduling data of public libraries under the condition of network environment and cultural construction is given as illustrated in the following mathematical model:(18)Vu,i=Di−Di++Di−,V.j¯=Ri+Ri++Ri−.To sum up, an adaptive fusion clustering processing model of public library’s massive resources under the condition of network environment and culture construction is constructed, and the fuzzy scheduling and feature mining of public library’s massive resources under the condition of network environment and culture construction are accomplished through implementing the correlation statistical feature detection technique [22, 23], so as to improve the sharing level of public library’s massive resources under the condition of network environment and culture construction [24].


## 3.2. Sharing and Scheduling of Mass Resources in Public Libraries

Under the constraint of association rules, cloud computing is adopted to obtain the association rule distribution parameter setY and fuzzy C-means clustering center vector of public library’s massive resource information under the condition of network environment and cultural construction. Thus, obtaining the similarity distribution mapping function of public library’s massive resource information under the condition of network environment and cultural construction under cloud computing is computed using the following equation:(19)SimX,Y=CosX,Y=CX⋅CYCX⋅CY.The information storage center management database of public library’s massive resources under the condition of network environment and culture construction is established, and the fuzzyC-means clustering scheme and procedure are implemented in the database to cluster the massive resources of public library under the condition of network environment and culture construction, and the adaptive updating formula of public library’s massive resource sharing scheduling under the condition of network environment and culture construction is obtained as follows:(20)Rdit−1=minRs,maxRdit+βnt−Nit,(21)Nit=j:xjt−xit<Rdi;lit<ljt.where xjt represents the distribution position of public library’s massive resource sharing big data prior data in the h sensor node of the t generation under the condition of network environment and culture construction. In the same way, the variable ljt represents the mutual information feature quantity of the first sensor node of the generation. Combined with the fuzzy decision classification model, the adaptive scheduling of public library’s massive resource sharing under the condition of network environment and culture construction is carried out, and the scheduling formula is as follows:(22)xit=xit−1+sxjt−1−xit−1xjt−1−xit−1.The autoregressive moving average model is adopted to design the distributed database of public library’s massive resource sharing under the condition of network environment and culture construction, and the probability confidence interval and rejection interval are constructed. Combined with the cloud computing technology, the sharing and classified management scheduling of public library’s massive resources under the condition of network environment and culture construction are realized.


## 4. Simulation Tests and Results

In order to examine the application performance of the anticipated technique in the scheduling of mass resource sharing in public libraries under the condition of network environment and culture construction, an experimental analysis was carried out. The Matlab simulation software was used to design the algorithm of mass resource sharing in public libraries under the condition of network environment and culture construction, and the initial check frequency of mass resource sharing and big data sharing in public libraries under the condition of network environment and culture construction was set as 120 Hz [25]. Under the condition of network environment and culture construction, the directional statistical feature distribution set of public library’s massive resources association rules is 400. Moreover, the information embedding dimension of feature space is m = 40, and the sampling time delay of public library’s massive resources under the condition of network environment and culture construction is ω = 30 ms; the self-adaptive scheduling weight of public library’s massive resources under the condition of network environment and culture construction is 0.9. Similarly, we use fuzzy correlation coefficient and sample mean square error (RMSE) to test the sharing performance of massive resources of public libraries under the conditions of network environment and cultural construction [26]. The RMSE metric is defined as follows:(23)RMSEx¯k=1NMC∑i=1NMCxki−x¯k2,where NMC represents the number of public library’s massive resources samples under the condition of network environment and culture construction. Similarly, the variable xki represents the original sample value of public library’s massive resource sharing under the condition of network environment and culture construction, and xk represents the average value of public library’s massive resource sharing under the condition of network environment and culture construction [27, 28]. Conferring to the aforementioned simulation parameters, assumptions, environment, and parameter settings, the mass resource sharing design of public libraries under the condition of network environment and culture construction is accomplished, and the original mass resource big data distribution model of public libraries under the condition of network environment and culture construction is obtained as shown in Figure 2.Figure 2
Spatial distribution of massive resources and big data in public libraries under the condition of network environment and cultural construction.Taking the massive resource data of public libraries under the condition of network environment and culture construction in Figure2 as the sample set, the fuzzy scheduling and feature mining of massive resources of public libraries under the condition of network environment and culture construction are performed through implementing the correlation statistical feature detection scheme, and the information storage center management database of massive resources of public libraries under the condition of network environment and culture construction is established. In the database, the fuzzy C-means clustering scheme is implemented to cluster the massive resources of public libraries under the condition of network environment and culture construction, and the data clustering outcomes are given in Figure 3.Figure 3
Clustering results of massive resources of public libraries under the condition of network environment and cultural construction.Figure3 shows that the clustering of public libraries’ massive resource sharing under the condition of network environment and culture construction is good, and the sharing level is improved. By testing the sharing level of public libraries’ massive resources under the condition of network environment and culture construction by different methods, the RMSE comparison outcomes are made known in Figure 4. Figure 4 displays that the error of public libraries’ massive resource sharing under the condition of network environment and culture construction by the proposed method is low, indicating that the sharing level is high.Figure 4
Comparison of sharing level.


## 5. Conclusions and Future Work

Under the cloud computing background, the optimization design of public library’s massive resource management under the condition of network environment and culture construction is carried out, and the large data distribution features of public library’s massive resources under the condition of network environment and culture construction are extracted. Combined with correlation feature information detection and fuzzy cluster analysis, the design of public library’s massive resource management and sharing under the condition of network environment and culture construction is carried out, and the sharing method of public library’s massive resources under the condition of network environment and culture construction based on cloud computing technology is put forward. Cloud computing scheme is implemented to collect the statistical information characteristics of public library’s massive resources under the condition of network environment and culture construction, and an adaptive fusion clustering processing model of public library’s massive resources under the condition of network environment and culture construction is constructed.The correlation statistical feature detection approach is implemented to carry out fuzzy scheduling and feature mining of public library’s massive resources under the condition of network environment and culture construction. The information storage center management database of public library’s massive resources under the condition of network environment and culture construction is established. The fuzzyC-means clustering technique is also implemented in the database to cluster the massive resources of public library under the condition of network environment and culture construction. Combined with cloud computing technology, the sharing and classified management scheduling of massive resources of public library under the condition of network environment and culture construction are realized. The research outcomes demonstrated that the anticipated approach has good performance and low error in sharing and classifying management of mass resources in public libraries under the condition of network environment and cultural construction.The deep learning network is still under development; thus, it is required to update the suggested assessment model in accordance with the most recent advancement in order to evaluate a huge quantity of data. The goal is to offer crucial technical assistance to increase the effectiveness of scheduling for enormous amount of resources. Similar to this, future study should examine deep neural networks and the effects of model activation functions. Although it is also possible that the deep learning algorithms are conducted in parallel, using the Spark framework, however, we believe that the computational time is still constrained on a single online machine. To increase the training efficiency in terms of computational times, big data technologies like edge computing should be leveraged, in the future.



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*Source: 8925897-2022-09-28.xml*