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1.
《Information processing & management》2022,59(5):103025
Since the patient is not quarantined during the conclusion of the Polymerase Chain Reaction (PCR) test used in the diagnosis of COVID-19, the disease continues to spread. In this study, it was aimed to reduce the duration and amount of transmission of the disease by shortening the diagnosis time of COVID-19 patients with the use of Computed Tomography (CT). In addition, it is aimed to provide a decision support system to radiologists in the diagnosis of COVID-19. In this study, deep features were extracted with deep learning models such as ResNet-50, ResNet-101, AlexNet, Vgg-16, Vgg-19, GoogLeNet, SqueezeNet, Xception on 1345 CT images obtained from the radiography database of Siirt Education and Research Hospital. These deep features are given to classification methods such as Support Vector Machine (SVM), k Nearest Neighbor (kNN), Random Forest (RF), Decision Trees (DT), Naive Bayes (NB), and their performance is evaluated with test images. Accuracy value, F1-score and ROC curve were considered as success criteria. According to the data obtained as a result of the application, the best performance was obtained with ResNet-50 and SVM method. The accuracy was 96.296%, the F1-score was 95.868%, and the AUC value was 0.9821. The deep learning model and classification method examined in this study and found to be high performance can be used as an auxiliary decision support system by preventing unnecessary tests for COVID-19 disease. 相似文献
2.
Due to a large variety of noisy information embedded in Web pages, Web-page classification is much more difficult than pure-text classification. In this paper, we propose to improve the Web-page classification performance by removing the noise through summarization techniques. We first give empirical evidence that ideal Web-page summaries generated by human editors can indeed improve the performance of Web-page classification algorithms. We then put forward a new Web-page summarization algorithm based on Web-page layout and evaluate it along with several other state-of-the-art text summarization algorithms on the LookSmart Web directory. Experimental results show that the classification algorithms (NB or SVM) augmented by any summarization approach can achieve an improvement by more than 5.0% as compared to pure-text-based classification algorithms. We further introduce an ensemble method to combine the different summarization algorithms. The ensemble summarization method achieves more than 12.0% improvement over pure-text based methods. 相似文献
3.
《The Journal of High Technology Management Research》2020,31(2):100389
Despite growing investments in Business Intelligence and Analytics (BI&A), the business value generation process associated with the adoption of these technologies is still unclear. Consequently, managers face difficulties in justifying such initiatives and subsequently evaluating their results. For companies that operate in extremely turbulent environments, the outcomes of BI&A investments may be even harder to estimate. In this study, we propose and statistically evaluate a causal model that connects the availability of BI&A resources and capabilities in a company to its operational marketing capabilities. Marketing processes are critical for the generation of innovations in products and services, and operational revenues, and thereby, for a firm's performance and competitiveness. In order to assess our model, we applied structural equation modeling techniques to data collected in multiple units of a large Brazilian telecommunications company during the worst economic and institutional crisis faced by the country. Our results suggest that the dynamic capabilities of a company fully mediates the positive effect of BI&A resources and capabilities on its marketing capabilities. In contrast to what is usually found in the literature, turbulence did not moderate the effect of dynamic capabilities on marketing capabilities. 相似文献
4.
《Information processing & management》2023,60(3):103271
Because of the rapid increase of data in the cloud of Amazon Web Service (AWS), the traditional methods for analyzing this data are not good and inappropriate, so unconventional methods of analysis have been proposed by many data scientists such as concurrent/ parallel techniques to meeting the requirements of performance and scalability entailed in such big data analyses. In this paper we are used Hadoop Map Reduce system that contains Hadoop Distributed File System (HDFS) and Hadoop cluster. We optimized it by combining it with five efficient Data Mining (DM) algorithms such as Support Vector Machine (SVM), Decision Tree (DT), Random Forest (RF), Correlative Naïve Bayes classifier (CNB), and Fuzzy CNB (FCNB) for strong analytics of cloud big data. The proposed system applied on product review data that taken form the cloud of AWS. The Evaluation of Hadoop Map Reduce done with important benchmarks as Mean Absolute Percentage Error (MPAE), Root Mean Square Error (RMSE), and runtime for word count, sort, inverted index. Also, the evaluation of DM models with Hadoop Map Reduce system done by using accuracy, sensitivity, specificity, memory, and running time. Experiments have shown that FCNB is effective in addressing the problem of big data. 相似文献
5.
Mergers and acquisitions: Their effect on the innovative performance of companies in high-tech industries 总被引：6，自引：0，他引：6
This study examines the post-M&A innovative performance of acquiring firms in four major high-tech sectors. Non-technological M&As appear to have a negative impact on the acquiring firm's post-M&A innovative performance. With respect to technological M&As, a large relative size of the acquired knowledge base reduces the innovative performance of the acquiring firm. The absolute size of the acquired knowledge base only has a positive effect during the first couple of years after which the effect turns around and we see a negative effect on the innovative performance of the acquiring firm. The relatedness between the acquired and acquiring firms’ knowledge bases has a curvilinear impact on the acquiring firm's innovative performance. This indicates that companies should target M&A ‘partners’ that are neither too unrelated nor too similar in terms of their knowledge base. 相似文献
6.
互联网的发展逐渐改变了人们的生活方式,电子邮件因其方便、快捷的特点已受到人们的青睐。但许多垃圾邮件同时也在网络中蔓延,占据了邮件服务器的大量存储空间,用户往往需要花费大量的时间去删除这些垃圾邮件。因此,研究邮件的自动过滤具有重要意义。邮件的自动过滤主要有基于规则和基于统计两种方式。而目前基于统计的过滤器中,常用的贝叶斯方法等是建立在经验风险最小化的基础之上,过滤器推广性能较差。支持向量机(SVM)是在统计学习理论的基础上发展而来的一种新的模式识别方法,在解决有限样本、非线性及高维模式识别问题中表现出许多特有的优势。它不仅考虑了对推广能力的要求,而且追求在有限信息的条件下得到最优结果。因此,本文将支持向量机应用于邮件过滤,实验证明过滤效果较好。 相似文献
7.
While much research has been directed at variables critical to successful R&D of new and high-technology products, much less work has been directed at factors crucial to success of these products when the firm attempts to enter the international marketplace. This study surveys Finnish technology firms and identifies those marketing method variables that are associated with successful versus unsuccessful attempts to enter the international marketplace. The rank order of importance of the different marketing methods will be presented. 相似文献
8.
《International Journal of Information Management》2017,37(5):400-416
As a key construct for the IS success model (DeLone & McLean (1992, 2003), information systems benefits for individuals (ISBI) has received considerable attention from researchers over the years. However, much remains to be explored to develop and validate the underlying theoretical dimensions for this crucial construct. Further, a major weakness of the extant research in this area is that most reported studies have been conducted in the context of individual IS application instead of the overall IS in the organization. To fill these gaps in research, we will first present a theoretical conceptualization of the ISBI construct, and then develop and validate a measurement scale for the construct. Drawing from the ERG theory (Alderfer, 1972), Job Characteristic Theory (Hackman & Oldham, 1975, 1976) and other theoretical perspectives, we developed a theory-based TJW framework which consists of three levels: Task performance, Job interaction, and Work enrichment. The nomological validity of the scale was then successfully demonstrated by a partial test of the IS success model using the ISBI measure and a measure of the overall IS use. Finally, we demonstrated the diagnostic power of the construct through an exploratory research model which showed that, while task performance benefits have insignificant effect on satisfaction, both job interaction benefits and work enrichment effects have substantial effects on satisfaction. These study results have thus deepened our understanding on the underpinnings of IS usage behaviors and contributed to the cumulated research on IS success. 相似文献
9.
《Information processing & management》2022,59(2):102845
Cognitive impairments like memory disorder and depressive disorders lead to fatal consequences if proper attention is not given to such health hazards. Their impact is extended to the socioeconomic status of the developed and low or middle-income countries in terms of loss of talented and skilled population. Additionally, financial burden is borne by the countries in terms of additional health budget allotment. This paper presents a novel strategy for early detection of cognitive deficiency to eliminate the economic repercussions caused by memory disorder and depressive disorders. In this work, Electroencephalogram (EEG) and a word learning neuropsychological test, i.e. California Verbal Learning Task (CVLT), are conjunctively used for memory assessment. The features of EEG and scores of CVLT are modeled by applying different machine learning techniques, namely K-Nearest Neighbor (KNN), Gaussian Naive Bayes (GNB), Decision Tree (DT), Random Forest (RF), and Support Vector Machine (SVM). Comparatively, experimental results have better classification accuracy than the existing schemes that considered EEG for estimating cognitive heuristics. More specifically, SVM attains the highest accuracy score of 81.56% among all machine learning algorithms, which can assist in the early detection of cognitive impairments. The proposed strategy can be helpful in clinical diagnosis of psychological health and improving quality of life as a whole. 相似文献
10.
Jieming Yang Yuanning Liu Xiaodong Zhu Zhen Liu Xiaoxu Zhang 《Information processing & management》2012
The feature selection, which can reduce the dimensionality of vector space without sacrificing the performance of the classifier, is widely used in text categorization. In this paper, we proposed a new feature selection algorithm, named CMFS, which comprehensively measures the significance of a term both in inter-category and intra-category. We evaluated CMFS on three benchmark document collections, 20-Newsgroups, Reuters-21578 and WebKB, using two classification algorithms, Naïve Bayes (NB) and Support Vector Machines (SVMs). The experimental results, comparing CMFS with six well-known feature selection algorithms, show that the proposed method CMFS is significantly superior to Information Gain (IG), Chi statistic (CHI), Document Frequency (DF), Orthogonal Centroid Feature Selection (OCFS) and DIA association factor (DIA) when Naïve Bayes classifier is used and significantly outperforms IG, DF, OCFS and DIA when Support Vector Machines are used. 相似文献
11.
【目的/意义】挖掘药物筛选工作中的隐性知识,借助机器学习的预测能力替代生物实验方法,减少制药流程的研发时间和经济成本。【方法/过程】提出一种面向知识发现的ADMET情报预测理论框架,以4种传统机器学习方法和2种集成学习方法,分别构建6种分类预测模型,提取药物的隐性知识,比较不同模型的优越性,评估最优模型的经济价值。【结果/结论】以药物分子描述符信息预测ADMET具有可行性,6种模型性能表现综合排序结果为随机森林、梯度提升决策树、Logistic回归、支持向量机、K近邻、高斯朴素贝叶斯。前沿信息技术能够有效应用于药物知识发现,信息经济学分析可预见创造可观收益,是未来制药工艺降本增效的重要手段。【创新/局限】未来应融合专家知识、追加试验验证、丰富参考指标。 相似文献
12.
Integrating knowledge across a firm's value chain (e.g. between R&D, marketing and manufacturing functions), which we denote “Knowledge Integration” (KI), has been consistently found to be a strong predictor of product innovation performance in the management literature. Such cross-functional integration does not occur by chance, but by design, as a result of managerial practices and organizational arrangements. The significant heterogeneity characterizing the diffusion of cross-functional integration across firms is suggestive of the well-known tension between internal and external diffusion of knowledge. In this paper, we argue that the hidden cost of KI is to expose firms to a higher risk of knowledge leakages and provide the first systematic empirical evidence of this apparent tension between internal and external knowledge flows. Based on data from the CMU Survey (one of the rare datasets offering observables on both sides of the tension for a representative set of R&D active firms in the US), we investigate the impact of knowledge spillovers to competitors on internal cross-functional knowledge integration involving the R&D function among manufacturing firms. We find that the intensity of (tacit) R&D knowledge spillovers at the industry-level has a negative and significant impact on the likelihood that firms adopt or achieve KI. Our results therefore suggest that firms may trade their optimal innovative performance against superior appropriability of their rents. 相似文献
13.
The provision of banking services on the Internet (e-banking) is growing but there is a lack of research related to the organisational issues involved in its adoption. This paper brings theory and practice together by synthesising the existing literature with real-life experience of a UK bank. Two questions motivated this research. First, what is the experience of organisations in adopting e-banking? Second, what are the organisational factors which are critical to the success in e-banking adoption? A case study research approach was used to investigate organisational critical success factors in e-banking adoption at The Woolwich bank. The factors found to be most critical for success in e-banking included: understanding customers, organisational flexibility, availability of resources, systems security, established brand name, having multiple integrated channels, e-channel specific marketing, systems integration, systematic change management, support from top management, and good customer services. We concluded that banks need to implement considerable organisational changes in order to web-enable themselves. The main focus of their e-commerce strategy should be to integrate the e-banking channel with other service delivery channels to maximise benefits. 相似文献
14.
《International Journal of Information Management》2014,34(2):272-284
Company movements and market changes often are headlines of the news, providing managers with important business intelligence (BI). While existing corporate analyses are often based on numerical financial figures, relatively little work has been done to reveal from textual news articles factors that represent BI. In this research, we developed BizPro, an intelligent system for extracting and categorizing BI factors from news articles. BizPro consists of novel text mining procedures and BI factor modeling and categorization. Expert guidance and human knowledge (with high inter-rater reliability) were used to inform system development and profiling of BI factors. We conducted a case study of using the system to profile BI factors of four major IT companies based on 6859 sentences extracted from 231 news articles published in major news sources. The results show that the chosen techniques used in BizPro – Naïve Bayes (NB) and Logistic Regression (LR) – significantly outperformed a benchmark technique. NB was found to outperform LR in terms of precision, recall, F-measure, and area under ROC curve. This research contributes to developing a new system for profiling company BI factors from news articles, to providing new empirical findings to enhance understanding in BI factor extraction and categorization, and to addressing an important yet under-explored concern of BI analysis. 相似文献
15.
Integrating marketing and R&D inputs is one of the fundamental challenges in managing innovation. In the pharmaceutical industry, considering its reputed ‘technology push’ model of innovation, the challenge of integrating marketing and R&D could hardly be greater. Thus, the recent trend among pharmaceutical firms of implementing Marketing/R&D integrating mechanisms calls for upgrading our conceptualization of the innovation process in this industry. It also raises important questions regarding Marketing's contribution in new product development, and how to organize to assure that contribution is leveraged. We use the case of a pharmaceutical firm which recently implemented Marketing/R&D integrating mechanisms to examine Marketing's new roles. We find that the extreme conditions surrounding innovation in the pharmaceutical industry, notably the need to cope with Knightean uncertainty, highlight important contributions of Marketing input in R&D that deserve more attention. We suggest that Marketing's most important contribution under these conditions lies in ‘not getting it wrong’ rather than ‘getting it right,’ in setting minimum criteria in project evaluations rather than definite targets, and in refocusing the attention of R&D staff through the very process of providing this input. Given the value of these contributions, modern pharmaceutical firms would indeed be ill advised to think of drug discovery as merely a linear process. Drug development has become an interactive process where the timing, type and impact of Marketing involvement is balanced and managed via certain organizational mechanisms throughout the R&D process, which is an iterative one. 相似文献
16.
《Information processing & management》2023,60(2):103231
During coronavirus (SARS-CoV2) the number of fraudulent transactions is expanding at a rate of alarming (7,352,421 online transaction records). Additionally, the Master Card (MC) usage is increasing. To avoid massive losses, companies of finance must constantly improve their management information systems for discovering fraud in MC. In this paper, an approach of advancement management information system for discovering of MC fraud was developed using sequential modeling of data depend on intelligent forecasting methods such as deep Learning and intelligent supervised machine learning (ISML). The Long Short-Term Memory Network (LSTM), Logistic Regression (LR), and Random Forest (RF) were used. The dataset is separated into two parts: the training and testing data, with a ratio of 8:2. Also, the advancement of management information system has been evaluated using 10-fold cross validation depend on recall, f1-score, precision, Mean Absolute Error (MAE), Receiver Operating Curve (ROC), and Root Mean Square Error (RMSE). Finally various techniques of resampling used to forecast if a transaction of MC is genuine/fraudulent. Performance for without re-sampling, with under-sampling, and with over-sampling is measured for each Algorithm. Highest performance of without re-sampling was 0.829 for RF algorithm-F score. While for under-sampling, it was 0.871 for LSTM algorithm-RMSE. Further, for over-sampling, it was 0.921 for both RF algorithm-Precision and LSTM algorithm-F score. The results from running advancement of management information system revealed that using resampling technique with deep learning LSTM generated the best results than intelligent supervised machine learning. 相似文献
17.
《Information processing & management》2022,59(6):103086
The quantity of electronic bank data grows exponentially with development of Information Technology (IT). The size of these data is impossible for traditional database and human analyst to come up with interesting information that will help in process of decision making. Management Information System (MIS) based Data warehouse (DW) and Data Mining (DM) techniques support the development of IT and process of management decision-making. But the traditional DW size make the query complex, which may cause unacceptable delay in decision support queries. Thus, in this paper an Efficient Electronic Bank MIS based DW and Mining Processing (EEBMIS-DWMP) was developed with cluster and non-cluster indexed view to provide decision-makers with both best response time and precise information. Also, analysis of the multilayer perception neural network, naïve Bayes, random forest, logistic regression, support vector machine and C5.0 on a real-world data of bank was done to improve effectiveness for campaign by analyzing the most useful features that influence campaign success. Results offer how the proposed EEBMIS-DWMP developed bank organizations by comparing performance of system with and without index view in terms of balance accuracy, accuracy, precision, recall, mean absolute error, root mean square error, F measure and running time. Conclusions from results offers that EEBMIS-DWMP can construct a database for each customer, a storage system that integrates data from a variety of sources into a single unified framework, decrease errors and time required to prepare financial reports, quickly access for information, analysis of data in multivariate, accurate prediction of competent, profitability segmentation. 相似文献
18.
We study several machine learning algorithms for cross-language patent retrieval and classification. In comparison with most of other studies involving machine learning for cross-language information retrieval, which basically used learning techniques for monolingual sub-tasks, our learning algorithms exploit the bilingual training documents and learn a semantic representation from them. We study Japanese–English cross-language patent retrieval using Kernel Canonical Correlation Analysis (KCCA), a method of correlating linear relationships between two variables in kernel defined feature spaces. The results are quite encouraging and are significantly better than those obtained by other state of the art methods. We also investigate learning algorithms for cross-language document classification. The learning algorithm are based on KCCA and Support Vector Machines (SVM). In particular, we study two ways of combining the KCCA and SVM and found that one particular combination called SVM_2k achieved better results than other learning algorithms for either bilingual or monolingual test documents. 相似文献
19.
在文献综述的基础上将低碳营销创新划分为渐进式低碳营销创新、以技术为基础的变革型低碳营销创新、以市场为基础的变革型低碳营销创新三种低碳营销创新方式,并将服务/市场配适、服务传递品质和营销沟通效果作为中间变量构建了低碳营销创新方式与营销绩效的关系理论模型,以国内261家服务业企业为样本,对模型进行实证检验。研究发现:渐进式低碳营销创新对营销绩效的直接正向影响不显著,但可以通过服务传递品质和营销沟通效果对营销绩效施加间接正向影响;以技术为基础的变革型低碳营销创新对营销绩效的直接正向影响不显著,但可以通过服务/市场配适、服务传递品质和营销沟通效果对营销绩效施加间接正向影响;以市场为基础的变革型低碳营销创新对营销绩效有显著的直接正向影响。 相似文献