Subjects: Library Science，Information Science >> Library Science submitted time 2023-10-08 Cooperative journals: 《知识管理论坛》
Abstract： [Purpose/significance] The research of productivity, influence, competitiveness and international cooperation funded by Beijing Natural Science Foundation during the “12th Five-Year Plan” period is analyzed, which will provide the basis for management. [Method/process] By InCites database, we analyzed the funding situation in recent 10 years. [Result/conclusion] The change trend of funding project outcomes, discipline structure and characteristics were studied. Compared with “11th Five-Year”, the fund investment was increased by 81.4%, the total amount of the application was increased by 53.1%, and the amount of funding was increased by 60%. During the “12th Five-Year Plan” period, the number of highly cited papers has been increased from 10 to 115, hot papers realize “zero” breakthrough, and the number of international cooperation papers is 5.6 times of that of the “11th Five-Year Plan” period. The dominant discipline mainly focuses on the field of chemistry, engineering, materials science, computer science, microbiology science. Environment, ecology and clinical medicine may grow to be advantage disciplines in the future. The suggestion is proposed to improve the competitiveness and influence of scientific research that further optimizes the discipline layout, improve the international cooperation, strengthen the guidance and evaluation on the “quality” of papers.
Subjects: Library Science，Information Science >> Information Science submitted time 2023-04-01 Cooperative journals: 《图书情报工作》
Abstract： [Purpose/significance] By means of the classification and circulation data of library collection, the paper finds the close correlation between reader characteristics and library collection circulation, establish the relationship model. And through model fitting and prediction, this study explores the implicit rule between reader and library circulation which provides technical and means support for the intelligent management of library.[Method/process] Firstly, this paper used clustering and correlation analysis techniques to extract the macroscopic observable characteristics of readers, constructed the direct and indirect mapping relationship between reader characteristics and book classification, and then constructed the regression model of the circulation of reader characteristics and classified books, and verified the validity of the model and optimized the goodness of fit of the model. According to the effective model, this paper explored the trend change of library circulation, and sum up the underlying rules of knowledge construction of the macroscopic characteristics of readers, as well as the impact on the circulation of books.[Result/conclusion] There are 3 classification characteristics of readers, namely, the professional learning direction representing the social role requirements of readers, the enrollment batch representing the interaction effect between readers and the number of readers, which can effectively fit and predict the book circulation. The prediction results show that the model has high accuracy and can be used as an effective tool to provide reliable technical support for library to develop knowledge service.
Subjects: Computer Science >> Integration Theory of Computer Science submitted time 2019-04-01 Cooperative journals: 《计算机应用研究》
Abstract： Internet advertising effectiveness evaluation is the core issue of online marketing. At present, the evaluation criteria of Internet advertising effectiveness are different. However, the evaluation methods have problems such as single source of information, no difference in falsehood, and global assumptions, which poses great challenges to the evaluation of Internet advertising effectiveness. Finding a new evaluation index to measure the effectiveness of Internet advertising has become an urgent task. This paper first proposes the concept of impression space innovatively as a more effective evaluation index of webpage advertising effects to solve the single problem of information source. Secondly, this paper analyzes the impact of user types, behaviors, behavioral processes and other characteristics on the evaluation criteria of Internet advertising effectiveness, and eliminates the evaluation bias caused by the user's indifference hypothesis. Thirdly, this paper introduces the local characteristics of web pages, and analyzes the influence of factors such as page layout, advertisement and page content relevance on Internet advertising effects to eliminate global assumptions. Finally, this paper constructs an impression space model based on multimodal features to predict the effectiveness of Internet advertising. The experimental results show that the accuracy rate of the impression space proposed by this paper is significantly improved to 92.4%. Moreover, the prediction results of the impression space model are not only more accurate and scientific, but also have obvious interpretability.
Subjects: Computer Science >> Integration Theory of Computer Science submitted time 2018-06-19 Cooperative journals: 《计算机应用研究》
Abstract： Chronic obstructive pulmonary disease (COPD) is a chronic lung disease that can lead to a gradual decline in respiratory function. Therefore, big data analysis and algorithms are needed to help doctors diagnose diseases more accurately. At present, there are limitations to the study of COPD: On the one hand, the research results only use data to analyze the impact of single features on the disease; on the other hand, the research results are only verified by simple algorithm models for case data. Therefore, this paper proposes a COPD multi-dimensional feature extraction and integrated diagnosis method. First, the MDF-RS algorithm is proposed to extract the optimal combination of multi-dimensional features. Secondly, the DSA-SVM integrated model is proposed to construct the classifier for diagnosis and prediction. Finally, the cross-validation method is used to verify the accuracy and other performance indicators. The experimental comparison shows the effectiveness of the proposed algorithm.
Subjects: Computer Science >> Integration Theory of Computer Science submitted time 2018-05-18 Cooperative journals: 《计算机应用研究》
Abstract： According to the fact that civil aviation emergency cannot effectively evaluate causality and correlation analysis, this paper proposed a causal analysis method for civil aviation emergencies based on Bayesian Network. The method introduces Bayesian theory on the basis of the domain ontology of civil aviation emergency management. Firstly, the Bayesian network realizes the transformation of concepts, relations and instances in domain ontology with rules design. Then construct the conditional probability table for Bayesian network nodes using Bayesian network knowledge synthesis algorithm E-IPFP, and calculate the probability relationship between parent nodes and child nodes hrough the message passing mechanism, to obtain the probability distribution of civil aviation incidents causation. This paper adopts the civil aviation emergency management domain ontology and the world civil aviation accident investigation tracking report as experimental data, gives爐he燼nalysis of the causal relationship between civil aviation emergencies, which provides the method to support the correlation analysis and reasoning of unexpected events based on large data.
Subjects: Computer Science >> Integration Theory of Computer Science submitted time 2018-05-02 Cooperative journals: 《计算机应用研究》
Abstract： In view of the problems of topic transfer and the existence of a large number of short text in the dialogue content in open domain dialogue systems, the traditional similarity-based processing method has many limitations. This paper proposeed an innovative method, which is based on the relevance of the sentences to determine whether the dialogue topic transfer, and compares the difference between the correlation-based and the similarity-based methods in revealing the relationship between sentences. Furthermore, this paper presents a correlation-based algorithm to calculate the correlation of words and apply it to segment topics of sentences, and this can address some challenges of topic transfer detection. Comparing with existing methods, the experimental results demonstrate the superior performance of the correlation-based method in this paper.
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