关联规则的增量更新算法研究     

富志伟 《人天科学研究》2010,(8):52-54

关联规则是数据挖掘领域的一个重要分支。随着数据库的不断变化,关联规则的增量更新变得尤为重要。为了更好地对关联规则进行有效的更新,对已经提出的经典的关联规则更新算法FUP和IUA算法进行分析,指出其优缺点;提出了一个改进的关联规则算法PFUP。该算法减少了候选项集数目,从而减少扫描数据库D的次数,提高了效率。  相似文献   

新兴交叉学科科技管理平台工作体系研究     

高崴  姚毓春 《科技管理研究》2021,41(4):104-108

论述新兴交叉学科及其科技管理平台和工作体系的内涵、特点及发展趋势,认为新兴交叉学科发展需要与其特点相适应的平台,平台建设也需要与其特点相适应的工作体系。研究发现,目前我国大学仅依托院系的单一组织形式面对新兴交叉学科发展,逐渐暴露出观念不足、体制机制不健全、科研自主权不充分、资源投入不持久、科研人员意愿不强、合作方式单一等诸多问题,问题的核心是没有构建与其相适应的科技管理工作体系。进一步从模式、理念、机制、人员4个角度入手,提出加强和优化高校新兴交叉学科科技管理平台建设发展路径,包括原有学院转型等4种模式、发展规划和生态目标制定、建立国际合作和联合攻关机制等5种工作机制以及联合聘任专家等4种人才管理方式。  相似文献   

国家创新体系的构建与评估:基于和谐管理理论的系统探讨   总被引：2，自引：0，他引：2  

王亚刚  席酉民 《中国软科学》2007,(3):53-58,75

国家创新体系（NIS）是近年来国内外理论界与实践界探讨较多的热点问题之一。在理论界，国家创新体系的构建和评估是NIS研究的两条主线。本文针对NIS构建及评估问题的复杂性以及国内该方面现有研究的不足，基于NIS实践，引入应对多变环境下复杂管理问题的和谐管理理论作为构建和评估国家创新体系的理论基础及理论支撑。基于该理论，本文深入探讨了国家创新体系构建的内在机理及微观机制，并建立了国家创新体系评估的系统的参考框架。本文拟运用一种新的视角和方式去完善国内现有的国家创新体系研究。  相似文献   

A twin data-driven approach for user-experience based design innovation     

《International Journal of Information Management》2023

Data-driven innovation has received increasing attention, which explores big data technologies to gain more insights and advantages for product design. In user experience (UX) based design innovation, user-generated data and archived design documents are two valuable resources for various design activities such as identifying opportunities and generating design ideas. However, these two resources are usually isolated in different systems. Additionally, design information typically represented based on functional aspects is limited for UX-oriented design. To facilitate experience-oriented design activities, we propose a twin data-driven approach to integrate UX data and archived design documents. In particular, we aim to extract UX concepts from product reviews and design concepts from patents respectively and to discover associations between the extracted concepts. First, a UX-integrated design information representation model is proposed to associate capabilities with key elements of UX at the concept, category, and aspect levels of information. Based on this model, a twin data-driven approach is developed to bridge experience information and design information. It contains three steps: experience aspect identification using an attention-based LSTM (Long short-term memory) network, design information categorization based on topic clustering using BERT (Bidirectional Encoder Representations from Transformers) and LAD (Latent Dirichlet allocation) model, and experience needs and design information integration by leveraging word embedding techniques to measure concept similarity. A case study using healthcare-related experience and design information has demonstrated the feasibility and effectiveness of this approach.  相似文献   

Artificial intelligence implication on energy sustainability in Internet of Things: A survey     

《Information processing & management》2023,60(2):103212

The massive number of Internet of Things (IoT) devices connected to the Internet is continuously increasing. The operations of these devices rely on consuming huge amounts of energy. Power limitation is a major issue hindering the operation of IoT applications and services. To improve operational visibility, Low-power devices which constitute IoT networks, drive the need for sustainable sources of energy to carry out their tasks for a prolonged period of time. Moreover, the means to ensure energy sustainability and QoS must consider the stochastic nature of the energy supplies and dynamic IoT environments. Artificial Intelligence (AI) enhanced protocols and algorithms are capable of predicting and forecasting demand as well as providing leverage at different stages of energy use to supply. AI will improve the efficiency of energy infrastructure and decrease waste in distributed energy systems, ensuring their long-term viability. In this paper, we conduct a survey to explore enhanced AI-based solutions to achieve energy sustainability in IoT applications. AI is relevant through the integration of various Machine Learning (ML) and Swarm Intelligence (SI) techniques in the design of existing protocols. ML mechanisms used in the literature include variously supervised and unsupervised learning methods as well as reinforcement learning (RL) solutions. The survey constitutes a complete guideline for readers who wish to get acquainted with recent development and research advances in AI-based energy sustainability in IoT Networks. The survey also explores the different open issues and challenges.  相似文献   

RGAN-EL: A GAN and ensemble learning-based hybrid approach for imbalanced data classification     

《Information processing & management》2023,60(2):103235

Imbalanced sample distribution is usually the main reason for the performance degradation of machine learning algorithms. Based on this, this study proposes a hybrid framework (RGAN-EL) combining generative adversarial networks and ensemble learning method to improve the classification performance of imbalanced data. Firstly, we propose a training sample selection strategy based on roulette wheel selection method to make GAN pay more attention to the class overlapping area when fitting the sample distribution. Secondly, we design two kinds of generator training loss, and propose a noise sample filtering method to improve the quality of generated samples. Then, minority class samples are oversampled using the improved RGAN to obtain a balanced training sample set. Finally, combined with the ensemble learning strategy, the final training and prediction are carried out. We conducted experiments on 41 real imbalanced data sets using two evaluation indexes: F1-score and AUC. Specifically, we compare RGAN-EL with six typical ensemble learning; RGAN is compared with three typical GAN models. The experimental results show that RGAN-EL is significantly better than the other six ensemble learning methods, and RGAN is greatly improved compared with three classical GAN models.  相似文献   

PVE: A log parsing method based on VAE using embedding vectors     

《Information processing & management》2023,60(5):103476

Log parsing is a critical task that converts unstructured raw logs into structured data for downstream tasks. Existing methods often rely on manual string-matching rules to extract template tokens, leading to lower adaptability on different log datasets. To address this issue, we propose an automated log parsing method, PVE, which leverages Variational Auto-Encoder (VAE) to build a semi-supervised model for categorizing log tokens. Inspired by the observation that log template tokens often consist of words, we choose common words and their combinations to serve as training data to enhance the diversity of structure features of template tokens. Specifically, PVE constructs two types of embedding vectors, the sum embedding and the n-gram embedding, for each word and word combination. The structure features of template tokens can be learned by training VAE on these embeddings. PVE categorizes a token as a template token if it is similar to the training data when log parsing. To improve efficiency, we use the average similarity between token embedding and VAE samples to determine the token type, rather than the reconstruction error. Evaluations on 16 real-world log datasets demonstrate that our method has an average accuracy of 0.878, which outperforms comparison methods in terms of parsing accuracy and adaptability.  相似文献   

逆向工程及其关键技术概述   总被引：3，自引：0，他引：3  

张艳君 《科技广场》2005,(1):11-13

逆向工程是一门集CAD、激光、精密机械、数控及图像采集与处理为一体的新技术,在工业领域中,逆向工程技术有着广泛的应用前景,利用逆向工程技术可以给现代工业带来巨大变化。本文简要介绍了逆向工程的基本内容及其与传统正向工程的区别,同时简述了逆向工程在工业领域的应用范围。详细地介绍了在逆向工程的四个基本阶段中所涉及到的关键技术,如三维数据采集方法、模型重构等,总结并分析了该领域需要重点解决的问题。  相似文献   

基于SOM网络聚类的数据清洗技术     

喻金平  徐琴 《科技广场》2005,(8):57-59

在数据装入数据仓库之前,应该对数据进行数据清洗.而数据清洗的核心工作就是清洗近似重复记录.聚类是将相似度高的数据对象聚集到一个类中,于是我们提出将该技术用于近似重复记录的发现上.本文主要介绍如何将SOM网络聚类强大的学习功能及良好的自组织性、自适应性和鲁棒性应用到数据清洗中。  相似文献   

基于分布式数据库的房地产管理信息系统的设计与实现     

张连福  何月顺 《科技广场》2005,(8):104-105

本文对房地产管理信息系统设计方案中的分布式数据库技术进行了详细阐述,包括分布式数据库的设计原则、系统结构、分布式查询与数据更新等内容.  相似文献