搜索结果: 1-14 共查到“管理学 Topic”相关记录14条 . 查询时间(0.097 秒)
A Supervised Neural Autoregressive Topic Model for Simultaneous Image Classification and Annotation
ASupervised Neural Autoregressive Topic Model Simultaneous Image Classification Annotation
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2013/6/17
Topic modeling based on latent Dirichlet allocation (LDA) has been a framework of choice to perform scene recognition and annotation. Recently, a new type of topic model called the Document Neural Aut...
Joint Topic Modeling and Factor Analysis of Textual Information and Graded Response Data
Factor analysis topic model personalized learning machine learning block coordinate descent
<
2013/6/14
Modern machine learning methods are critical to the development of large-scale personalized learning systems that cater directly to the needs of individual learners. The recently developed SPARse Fact...
Scalable Text and Link Analysis with Mixed-Topic Link Models
Document classification Community detection Topic mod-eling Link prediction Stochastic block model
<
2013/5/2
Many data sets contain rich information about objects, as well as pairwise relations between them. For instance, in networks of websites, scientific papers, and other documents, each node has content ...
Topic Discovery through Data Dependent and Random Projections
Topic Discovery through Data Dependent and Random Projections
<
2013/4/27
We present algorithms for topic modeling based on the geometry of cross-document word-frequency patterns. This perspective gains significance under the so called separability condition. This is a cond...
A non-parametric mixture model for topic modeling over time
non-parametric mixture model topic modeling over time
<
2012/9/17
A single, stationary topic model such as la-tent Dirichlet allocation is inappropriate for modeling corpora that span long time peri-ods, as the popularity of topics is likely to change over time. A n...
基于“Topic”的语义信息组织与图书馆学的经典Subject理论密不可分，可将其视为较为抽象化的Subject理论在语义Web环境下的一种“演化”和实用化的主题技术。文章首先解读Subject和Topic的概念，并概述两种基于Topic的国际标准技术，即Topic Maps和DITA；其次，简要描述Topic Maps的技术和应用，并重点介绍在图书馆界鲜为人知的DITA技术及其应用；再次，对基于...
“基于Topic的语义化文献信息组织”
Topic 语义化文献 信息组织
<
2012/6/18
迈向知识服务是数字图书馆的选择。然而，什么是知识服务？数字图书馆应当或能提供怎样的知识服务？这不是某一理论体系可以解决的问题，是需要融合各种理论的新模型、新框架。同时，知识服务是实实在在面向用户的最佳实践，如何将知识服务体现在数字图书馆应用系统之上？这就是本期的话题（topic）。我们希望通过探讨“基于Topic的语义化信息文献组织”来构建实用化的知识服务系统。
Statistical Topic Models for Multi-Label Document Classification
Topic Models LDA Multi-Label Classification Document Modeling
<
2011/7/19
Machine learning approaches to multi-label document classification have (to date) largely relied on discriminative modeling techniques such as support vector machines. A drawback of these approaches i...
Machine learning approaches to multi-label document classification have (to date) largely relied on discriminative modeling techniques such as support vector machines. A drawback of these approaches i...
Supervised Topic Models
Supervised Topic Models latent Dirichlet allocation labelled documents
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2010/3/11
We introduce supervised latent Dirichlet allocation (sLDA), a
statistical model of labelled documents. The model accommodates a va-
riety of response types. We derive an approximate maximum-likeliho...
Syntactic Topic Models
Syntactic Topic Models Bayesian nonparametric model latent distributions
<
2010/3/11
The syntactic topic model (STM) is a Bayesian nonparametric model of language that discovers
latent distributions of words (topics) that are both semantically and syntactically coherent. The STM mode...
本文在介绍Topic Maps和web2.0的基础上，指出当前web2.0的应用存在语义缺陷，而主题图则有一个良好的语义模型，因此可引入主题图作为杠杆来撬动web2.0的语义。最后对Topic Maps在构建语义Blog、语义wiki、语义RSS、语义Tag中的应用进行了研究。
[摘要]利用主题图技术构建一个在线叙词表。在分析传统叙词表的词间关系及其不足的基础上，从现有叙词表中选取18个叙词作为研究样本，分析其词间关系并进行建模；最后结合新兴的主题图技术，用Ontopia公司提供的Ontopoly创建出主题图，并用Omnigator和Vizigator分别进行在线浏览和可视化呈现。
Topic Maps：撬动Web2.0的语义杠杆
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2007/8/9
Topic Maps：撬动Web2.0的语义杠杆
朱良兵(四川大学公共管理学院成都610064)
文 摘
本文在介绍Topic Maps和web2.0的基础上，指出当前web2.0的应用存在语义缺陷，而主题图则有一个良好的语义模型，因此可引入主题图作为杠杆来撬动web2.0的语义。最后对Topic Maps在构建语义Blog、语义wiki、语义RSS、语义Tag中的应用进行了研究。
关键字
主题图...