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针对遗传算法优化SOFM神经网络的不足,提出利用合作型协同进化遗传算法实现SOFM 神经网络优化的方法。其基本思想是：针对SOFM神经网络中存在的“死神经元”现象,在SOFM 神经网络中引入全局搜索能力很强的合作型协同进化遗传算法,这样既解决了分类结果对样本输入顺序的过分依赖,又实现了SOFM 神经网络在竞争过程中的全局最优性。将新算法用于矿井突水水源判定问题,结果表明,该算法具有较好的全局收敛性,且可在很大程度上避免“死神经元”现象。 相似文献
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研究了P2P直播系统网络模型,并在此基础上提出一种基于可信节点的半结构化的网络模型（SSPM）。该模型结合了结构化网络模型中的对相邻节点有序组织和混合式网络模型的快速搜索的优点,利用可信节点良好的时间恒定性和性能稳定性,使该新型模型在实际网络环境下能达到较优的性能。 相似文献
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基于科研论文作者合作方式,建立了一个作者科研合作网络模型。通过理论分析和仿真验证,网络模型节点的度分布（作者合作人数）符合幂率分布,该网络是一种无尺度网络模型。为了说明作者合作网络模型的有效性,对2001年1月-2006年12月期间发表在《情报科学》期刊上的科研论文进行统计,建立了作者合作网络。对作者合作网络进行数据分析,结果与网络模型结论一致,因此该模型可以很好描述作者合作网络的演化过程。 相似文献
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基于复杂网络的高技术虚拟产业集群网络演化模型与仿真研究 总被引：1，自引：0，他引：1
从复杂网络视角,分析了高技术虚拟产业集群网络及网络演化的内涵,建立了揭示网络演化机理的HTVIC网络演化框架模型。在此基础上,分析了包含增长、择优连接、自增长、反择优衰退的HTVIC网络演化规则,同时以BA无标度网络演化模型为基础,构建了HTVIC双向择优网络演化模型,并运用平均场理论对该网络演化模型度分布与幂指数进行了详细求解。最后运用Matlab对HTVIC网络演化过程进行了模拟仿真,得出HTVIC双向择优网络演化模型是一种无标度网络演化模型、具有无标度特征的结论。 相似文献
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《科学学与科学技术管理》2012,33(3)
从复杂网络视角,分析了高技术虚拟产业集群网络及网络演化的内涵,建立了揭示网络演化机理的HTVIC网络演化框架模型。在此基础上,分析了包含增长、择优连接、自增长、反择优衰退的HTVIC网络演化规则,同时以BA无标度网络演化模型为基础,构建了HTVIC双向择优网络演化模型,并运用平均场理论对该网络演化模型度分布与幂指数进行了详细求解。最后运用Matlab对HTVIC网络演化过程进行了模拟仿真,得出HTVIC双向择优网络演化模型是一种无标度网络演化模型、具有无标度特征的结论。 相似文献
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分析当前舆情建模研究现状,提出比较符合社会实际的人际关系网络模型,并对建立该网络模型的思路,网络节点的类型、属性和关系进行描述。在此基础上,根据不同节点类型设定了相应的舆情演化规则,建立了基于人际关系网络的舆情演化模型。 相似文献
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《Information processing & management》2001,37(4):639-657
The paper introduces a new method for the visualization of information retrieval. Angle attributes of a document are used to construct the angle–angle-based visual space. The retrieved documents are perceived, several traditional information retrieval evaluation models are visualized and interpreted, and new non-traditional retrieval control means based on the model are explored in the two-dimensional angle display space. The impacts of different metrics on the visualization of information retrieval are discussed. Ambiguity, future research directions and other relevant issues are also addressed. 相似文献
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This paper presents a probabilistic information retrieval framework in which the retrieval problem is formally treated as a statistical decision problem. In this framework, queries and documents are modeled using statistical language models, user preferences are modeled through loss functions, and retrieval is cast as a risk minimization problem. We discuss how this framework can unify existing retrieval models and accommodate systematic development of new retrieval models. As an example of using the framework to model non-traditional retrieval problems, we derive retrieval models for subtopic retrieval, which is concerned with retrieving documents to cover many different subtopics of a general query topic. These new models differ from traditional retrieval models in that they relax the traditional assumption of independent relevance of documents. 相似文献
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互联网和信息数字化的高度发展为信息查询带来了新的挑战,如何改善查询模式使用户从海量的数据中快速找到真正需要的信息成为了当前业界亟待解决的课题。本文描述了一种个性化信息服务模型,使用DeepWeb数据集成技术设计了一个图书馆数字资源个性化信息服务系统,实现了以用户为中心的图书馆信息服务。 相似文献
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网络环境下的信息检索与数据挖掘技术 总被引：1，自引：0，他引：1
首先对网络环境下信息检索的现状进行分析。主要介绍网络信息检索的代表工具一搜索引擎的工作原理、缺陷夏发展方向,引出数据挖掘技术。并进一步对WEB数据挖掘技术作了概要的介绍,阐明WEB数据挖掘技术是网络信息检索智能化的重要发展方向之一。最后,提出一个结合数据挖掘技术的新的搜索引擎结构模型。 相似文献
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《Information processing & management》2005,41(5):1207-1223
This paper talks about several schemes for improving retrieval effectiveness that can be used in the named page finding tasks of web information retrieval (Overview of the TREC-2002 web track. In: Proceedings of the Eleventh Text Retrieval Conference TREC-2002, NIST Special Publication #500-251, 2003). These methods were applied on top of the basic information retrieval model as additional mechanisms to upgrade the system. Use of the title of web pages was found to be effective. It was confirmed that anchor texts of incoming links was beneficial as suggested in other works. Sentence–query similarity is a new type of information proposed by us and was identified to be the best information to take advantage of. Stratifying and re-ranking the retrieval list based on the maximum count of index terms in common between a sentence and a query resulted in significant improvement of performance. To demonstrate these facts a large-scale web information retrieval system was developed and used for experimentation. 相似文献
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个性化信息检索技术综述 总被引：5，自引：0，他引：5
个性化信息检索技术是现代信息检索技术的新发展形式,也是提高现有信息检索系统的检索质量,更好满足用户要求的必然举措.本文从用户模式表达方法、个性化结果获取方法和结果呈现方法3个角度,对个性化信息检索技术的发展现状进行全面的分析,说明了现代个性化信息检索技术的特点,并指出未来个性化信息检索技术需要进一步解决的问题. 相似文献
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The classical probabilistic models attempt to capture the ad hoc information retrieval problem within a rigorous probabilistic framework. It has long been recognized that the primary obstacle to the effective performance of the probabilistic models is the need to estimate a relevance model. The Dirichlet compound multinomial (DCM) distribution based on the Polya Urn scheme, which can also be considered as a hierarchical Bayesian model, is a more appropriate generative model than the traditional multinomial distribution for text documents. We explore a new probabilistic model based on the DCM distribution, which enables efficient retrieval and accurate ranking. Because the DCM distribution captures the dependency of repetitive word occurrences, the new probabilistic model based on this distribution is able to model the concavity of the score function more effectively. To avoid the empirical tuning of retrieval parameters, we design several parameter estimation algorithms to automatically set model parameters. Additionally, we propose a pseudo-relevance feedback algorithm based on the mixture modeling of the Dirichlet compound multinomial distribution to further improve retrieval accuracy. Finally, our experiments show that both the baseline probabilistic retrieval algorithm based on the DCM distribution and the corresponding pseudo-relevance feedback algorithm outperform the existing language modeling systems on several TREC retrieval tasks. The main objective of this research is to develop an effective probabilistic model based on the DCM distribution. A secondary objective is to provide a thorough understanding of the probabilistic retrieval model by a theoretical understanding of various text distribution assumptions. 相似文献