共查询到20条相似文献，搜索用时 171 毫秒
1.
《International Journal of Information Management》2014,34(6):751-760
This paper will present new theoretical and applied solutions for intelligent data analysis and information management in the fields of cognitive economics. Intelligent data analysis and information management are performed by information systems called cognitive systems, dedicated for semantic interpretation of acquired business information. To interpret the meaning of the analysed data, complex linguistic algorithms must be used, based on which it is possible to find the core information elements for business processes forecasting and economical knowledge management. The presentation of selected methods of semantic data analysis in cognitive economy, which allow to perform both local and global information management forms the main subject of this paper. Here, semantic analysis methods are dedicated to cognitive economics problems, namely the interpretation, analysis and assessment of the meaning of selected sets of economic/financial ratios. The meaning of the interpreted data sets is assessed by analysing the layers of meaning contained in data analysed sets. Obtained semantic information may be used in future business processes evaluation and forecasting. 相似文献
2.
A variety of the web-mining techniques are now being extensively utilized to extract useful knowledge about customer behaviors on the Internet. However, the naive interpretation of the web-mining results would lead to poor decision on customer behaviors, which is likely to cause waste of time and efforts on managing electronic commerce strategy. To overcome this pitfall, this study proposes using the cognitive map-based interpretation of the web-mining results. Conventional approach to obtaining the web-mining results is based on the association rule approach (ARA), while the cognitive map approach (CMA) is believed to provide more robust support in interpreting the web-mining results. Therefore, to compare the interpretation capability of the two approaches, the four constructs such as perceived usefulness, causality, information richness, users’ attitude and intention to use the approaches are adopted in the research model and tested against the questionnaire data. The test results obtained through applying the structural equation models reveal that CMA is comparable to ARA and the cognitive map has a great potential in helping enrich the interpretation of the web mining results and build more effective Internet business strategy. 相似文献
3.
管理者在决策的过程中扮演着重要的角色,考察管理者认知特点的差异对于管理决策质量的影响具有重要的意义。本文引入认知闭合需要这个个体认知变量,来考察其对管理决策的影响。通过对144份有效问卷的数据分析作实证研究。结果表明,认知闭合需要负向影响管理决策质量。 相似文献
4.
本文首先回顾了现代企业管理理论的发展轨迹,进而引入"一体化管理"的五层模型。该模型阐释了企业如何以价值创造为核心展开企业的运作,是价值管理的概念模型。在此概念模型的基础上,立足于时代背景,结合电信运营企业现有的信息化发展现状,进一步整合分散在各个业务子系统的管理系统,打造电信运营企业的价值管理控制系统,使价值管理理念得以落地实施。 相似文献
5.
6.
Traditionally, recommender systems for the web deal with applications that have two dimensions, users and items. Based on access data that relate these dimensions, a recommendation model can be built and used to identify a set of N items that will be of interest to a certain user. In this paper we propose a multidimensional approach, called DaVI (Dimensions as Virtual Items), that consists in inserting contextual and background information as new user–item pairs. The main advantage of this approach is that it can be applied in combination with several existing two-dimensional recommendation algorithms. To evaluate its effectiveness, we used the DaVI approach with two different top-N recommender algorithms, Item-based Collaborative Filtering and Association Rules based, and ran an extensive set of experiments in three different real world data sets. In addition, we have also compared our approach to the previously introduced combined reduction and weight post-filtering approaches. The empirical results strongly indicate that our approach enables the application of existing two-dimensional recommendation algorithms in multidimensional data, exploiting the useful information of these data to improve the predictive ability of top-N recommender systems. 相似文献
7.
A novel H∞ filter design methodology has been presented for a general class of nonlinear systems. Different from existing nonlinear filtering design, the nonlinearities are approximated using neural networks, and then are modeled based on linear difference inclusions, which makes the structure of the desired filter simpler and parameter turning easier and has the advantages of guaranteed stability, numeral robustness, bounded estimation accuracy. A unified framework is established to solve the addressed H∞ filtering problem by exploiting linear matrix inequality (LMI) approach. A numerical example shows that the filtering error systems will work well against bounded error between a nonlinear dynamical system and a multilayer neural network. 相似文献
8.
Automatic text classification is the task of organizing documents into pre-determined classes, generally using machine learning algorithms. Generally speaking, it is one of the most important methods to organize and make use of the gigantic amounts of information that exist in unstructured textual format. Text classification is a widely studied research area of language processing and text mining. In traditional text classification, a document is represented as a bag of words where the words in other words terms are cut from their finer context i.e. their location in a sentence or in a document. Only the broader context of document is used with some type of term frequency information in the vector space. Consequently, semantics of words that can be inferred from the finer context of its location in a sentence and its relations with neighboring words are usually ignored. However, meaning of words, semantic connections between words, documents and even classes are obviously important since methods that capture semantics generally reach better classification performances. Several surveys have been published to analyze diverse approaches for the traditional text classification methods. Most of these surveys cover application of different semantic term relatedness methods in text classification up to a certain degree. However, they do not specifically target semantic text classification algorithms and their advantages over the traditional text classification. In order to fill this gap, we undertake a comprehensive discussion of semantic text classification vs. traditional text classification. This survey explores the past and recent advancements in semantic text classification and attempts to organize existing approaches under five fundamental categories; domain knowledge-based approaches, corpus-based approaches, deep learning based approaches, word/character sequence enhanced approaches and linguistic enriched approaches. Furthermore, this survey highlights the advantages of semantic text classification algorithms over the traditional text classification algorithms. 相似文献
9.
《Information processing & management》2020,57(6):102358
This paper will describe Transformative Computing technologies as a new area of modern information sciences, which plays crucial role in development future IT technologies. Transformative computing allow to join communication technologies, and data processing techniques with advanced AI solutions, which allow to analytically process and manage acquired data. It enhances possibilities of efficient data analysis, and thanks to the application of AI, opens a new areas of data exploration towards planning, decision supporting, and advanced secure information management in distributed systems. In this paper we'll focus on new possible areas of transformative computing applications, especially for semantic information processing, as well as cognitive data reasoning. 相似文献
10.
Guillermo Navarro-Arribas Vicenç Torra Arnau Erola Jordi Castellà-Roca 《Information processing & management》2012
The anonymization of query logs is an important process that needs to be performed prior to the publication of such sensitive data. This ensures the anonymity of the users in the logs, a problem that has been already found in released logs from well known companies. This paper presents the anonymization of query logs using microaggregation. Our proposal ensures the k-anonymity of the users in the query log, while preserving its utility. We provide the evaluation of our proposal in real query logs, showing the privacy and utility achieved, as well as providing estimations for the use of such data in data mining processes based on clustering. 相似文献
11.
In this paper, the robust fault detection filter (RFDF) design problems are studied for nonlinear time-delay systems with unknown inputs. Firstly, a reference residual model is introduced to formulate the robust fault detection filter design problem as an H∞ model-matching problem. Then appropriate input/output selection matrices are introduced to extend a performance index to the time-delay systems in time domain. The reference residual model designed according to the performance index is an optimal residual generator, which takes into account the robustness against disturbances and sensitivity to faults simultaneously. Applying robust H∞ optimization control technique, the existence conditions of the robust fault detection filter for nonlinear time-delay systems with unknown inputs are presented in terms of linear matrix inequality (LMI) formulation, independently of time delay. An illustrative design example is used to demonstrate the validity and applicability of the proposed approach. 相似文献
12.
A linear matrix inequality based mixed H2-dissipative type state observer design approach is presented for smooth discrete time nonlinear systems with finite energy disturbances. This observer is designed to maintain H2 type estimation error performance together with either H∞ or a passivity type disturbance reduction performance in case of randomly varying perturbations in its gain. A linear matrix inequality is used at each time instant to find the time-varying gain of the observer. Simulation studies are included to explore the performance in comparison to the extended Kalman filter and a previously proposed constant gain observer counterpart. 相似文献
13.
《Information processing & management》2022,59(3):102914
In the era of autonomous systems, the security is indispensable module for flexible computing environment. Due to increased computer power and network speed, a new computing paradigm, such as cognitive inspired computing, will emerge. Such a paradigm provides human-centered services that are convenient and enjoyable at any time, anywhere, and on any device. On the foundation of smart city environment, human computer interaction, intelligent services, and universal device connectivity, Cyber Physical Computing for Cyber Physical systems has recently been investigated. However, in this proposal, a cognitive inspired framework for securing CPS is scrutinized. The cognitive ability is conceded to the search engines by updating the PageRank ranking methodology. The proposed framework, named SecureCPS is trained with real time collective dataset for marking the relevancy of web page with the support the facial expressions. The eye regions are marked using Focal Point Detector algorithm. The framework is validated with machine learning models and resulted in achieving 98.51% accuracy and its outperforms the existing frameworks. 相似文献
14.
Extracting semantic relationships between entities from text documents is challenging in information extraction and important for deep information processing and management. This paper investigates the incorporation of diverse lexical, syntactic and semantic knowledge in feature-based relation extraction using support vector machines. Our study illustrates that the base phrase chunking information is very effective for relation extraction and contributes to most of the performance improvement from syntactic aspect while current commonly used features from full parsing give limited further enhancement. This suggests that most of useful information in full parse trees for relation extraction is shallow and can be captured by chunking. This indicates that a cheap and robust solution in relation extraction can be achieved without decreasing too much in performance. We also demonstrate how semantic information such as WordNet, can be used in feature-based relation extraction to further improve the performance. Evaluation on the ACE benchmark corpora shows that effective incorporation of diverse features enables our system outperform previously best-reported systems. It also shows that our feature-based system significantly outperforms tree kernel-based systems. This suggests that current tree kernels fail to effectively explore structured syntactic information in relation extraction. 相似文献
15.
《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
16.
This paper deals with the problems of robust delay-dependent stability and H∞ analysis for Markovian jump linear systems with norm-bounded parameter uncertainties and time-varying delays. In terms of linear matrix inequalities, an improved delay-range-dependent stability condition for Markovian jump systems is proposed by constructing a novel Lyapunov-Krasovskii functional with the idea of partitioning the time delay, and a sufficient condition is derived from the H∞ performance. Numerical examples are provided to demonstrate efficiency and reduced conservatism of the results in this paper. 相似文献
17.
《Information processing & management》2023,60(3):103286
Figures and tables in scientific articles serve as data sources for various academic data mining tasks. These tasks require input data to be in its entirety. However, existing studies measure the performance of algorithms using the same IoU (Intersection over Union) or IoU-based metrics that are used for natural situations. There is a gap between high IoU and detection entirety in scientific figures and tables detection tasks. In this paper, we demonstrate the existence of this gap and suggest that the leading cause is the detection error in the boundary area. We propose an effective detection method that cascades semantic segmentation and contour detection. The semantic segmentation model adopted a novel loss function to enhance the weights of boundary parts and a categorized dice metric to evaluate the imbalanced pixels in the segmentation result. Under rigorous testing criteria, the method proposed in this paper yielded a page-level F1 of 0.983 exceeding state-of-the-art academic figure and table detection methods. The research results in this paper can significantly improve the data quality and reduce data cleaning costs for downstream applications. 相似文献
18.
Using data generated by progressive nucleation mechanism on the cumulative fraction of citations of individual papers published successively by a hypothetical author, an expression for the time dependence of the cumulative number Lsum(t) of citations of progressively published papers is proposed. It was found that, for all nonzero values of constant publication rate ΔN, the cumulative citations Lsum(t) of the cumulative N papers published by an author in his/her entire publication career spanning over T years may be represented in distinct regions: (1) in the region 0 < t < Θ0 (where Θ0 ≈ T/3), Lsum(t) slowly increases proportionally to the square of the citation time t, and (2) in the region t > Θ0, Lsum(t) approaches a constant Lsum(max) at T. In the former region, the time dependence of Lsum(t) of an author is associated with three parameters, viz. the citability parameter λ0, the publication rate ΔN and his/her publication career t. Based on the predicted dependence of Lsum(t) on t, a useful scientometric age-independent measure, defined as citation acceleration a = Lsum(t)/t2, is suggested to analyze and compare the scientific activities of different authors. Confrontation of the time dependence of cumulative number Lsum(t) of citations of papers with the theoretical equation reveals one or more citation periods during the publication careers of different authors. 相似文献
19.