Semi-Supervised Learning: Input data is a mixture of labelled and unlabelled examples.
半监视学习：输入数据由带符号的和不带符号的组成。
Semi-Supervised Learning: Input data is a mixture of labelled and unlabelled examples.
无监督学习：输入数据不带标签或者没有一个已知的结果。
Semi-Supervised Learning : Input data is a mixture of labelled and unlabelled examples.
半监督学习：输入数据由带标记的和不带标记的组成。
A semi-supervised learning system was proposed based on ART (adaptive resonance theory).
根据自适应谐振理论提出了半监督学习自适应谐振理论系统。
In this paper, we discuss the problem of using semi-supervised learning method to do video semantic annotation.
本文讨论了利用半监督学习方法进行视频语义标注的问题。
The analysis of experimental data has proven that this algorithm has better effect on semi-supervised classification.
实验数据分析证明了该算法在进行半监督分类时具有比较好的效果。
Detailed descriptions and analytic experimental results of our semi-supervised SRL system will be displayed in this paper.
对于该系统的细节描述以及实验分析结果将在本论文中一一给出。
Our work in building such a complete semi-supervised SRL system will be helpful for further semantically study in Chinese.
作者关于建立了一个完整的半监督语义角色标注系统的工作，将对未来中文语义分析工作起到很大的帮助作用。
Semi-supervised learning - Combines both labeled and unlabeled examples to generate an appropriate function or classifier.
半分类学习-将标签与非标签用例劫后生成一个合适的函数或分类器。
Therefore, this algorithm has solved the problem of model updating in semi-supervised learning under appropriate conditions.
该算法在一定条件下解决了半监督学习环境下的模型更新问题。
The comparison and analysis of geometric information's impact on semi-supervised learning is performed through the experiments.
最后通过实验对比和分析了几种几何信息对半监督学习效果的影响。
This paper reviews the problem of semi-supervised learning the basic idea of the status quo, Summarized the current study difficult.
该文综述了半监督：学习问题的基本思想、研究现状，简述目前的研究困难。
The method takes advantage of semi-supervised thought to quantitate speech data and forms a code model with supervision information.
该方法利用半 监督的思想对方言语音数据进行矢量 量化，形成具有监督信息的码本模型。
Semi-supervised learning algorithms, which consider both labeled and unlabeled data, can improve learning effectiveness significantly.
半监督学习算法同时考虑有标记和无标记数据，能显著提升学习效果。
Experimental results show that Semi-supervised self-adaptative algorithm can better solve the real-time exception detection process issues.
实验表明，半监督自适用算法能较好地解决入侵检测的即时异常进程问题。
Compared to unsupervised clustering, semi-supervised clustering utilizes a small amount of given prior knowledge to guide the clustering process.
相比于无监督聚类分析，半监督聚类利用提供的少量监督信息协助指导聚类过程。
The ANN can derive a continuous-spread stability index to indicate the relative stability degree by means of a semi-supervised learning algorithm.
使用一个半监督学习算法，ANN可产生一个能够指示相对稳定度的连续分布的暂态稳定指标。
Experimental result demonstrates that compared with previously proposed semi-supervised clustering algorithm this method produces better clusters.
实验表明，该算法较之于已提出的半监督聚类算法，获得了更好的聚类性能。
The pairwise constraints are the most common prior knowledge, and many semi-supervised clustering algorithms are based on the type of constraints.
成对约束是先验知识中最普遍的，目前许多半监督聚类算法都基于此类约束形式。
So, the semi-supervised learning method by learning a small number of labeling samples and a large number of samples to establish classifier came into being.
如此，通过对少量已标记样本和大量未标记的样本进行学习从而建立分类器的半监督学习方法应运而生。
Semi-supervised learning methods including self-training and co-training were shown in the task of PPI on how to alleviate the tag burden as much as possible.
使用半监督学习方法中的自训练、协同训练方法，利用少量已标注样本和大量未标注样本来完成蛋白质关系抽取的任务。
Semi-supervised clustering algorithms use a small amount of supervision information in the form of labeled data or pairwise constraints to improve clustering performance.
半监督聚类通过利用少量有标号样本或成对约束等监督信息来提高聚类性能。
For learning document classification on line, the paper gives the semi-supervised learning fuzzy ART model (SLFART) based on adaptive resonance theory and the models algorithm.
为了对在线学习文档进行分类，本文根据自适应谐振理论给出了一个半监督学习模糊art模型(SLFART)及其算法。
How to make the effect of semi-supervised learning closed to or the same to the supervised learning by unlabeled samples information is the key of semi-supervised learning method.
如何利用未标记的视频样本信息达到类似于全监督学习的效果是半监督学习方法的关键。
Most of the existing semi-supervised clustering methods neglect the structural information of the data, while the few constraints available may degrade the performance of the algorithms.
现有的半监督聚类方法较少利用数据集空间结构信息，限制了聚类算法的性能。
Graph-based learning is a very active direction of semi-supervised learning in recent years. It describes the sample space by graph, and USES neighbors to spread label information in point cloud.
基于图的学习是近几年来半监督学习中一个相当活跃的方向，它用图来描述样本空间，利用近邻点的位置来控制标记信息的传播。
If the ultimate effect of the semi-supervised method is the same or close to the result of supervised learning method, the semi-supervised learning is more advantages in labor costs and achievement.
若其最终的学习效果与全监督学习方法的效果一致或接近，则在人工成本和实现上，半监督学习方法更具有优越性。
The method of product feature extraction and analysis can be divided into supervised machine learning methods, semi-supervised machine learning algorithms and unsupervised machine learning algorithm.
产品评价对象的提取与分析的方法主要分为有监督的机器学习方法、半监督的机器学习算法、无监督的机器学习算法。
The method of product feature extraction and analysis can be divided into supervised machine learning methods, semi-supervised machine learning algorithms and unsupervised machine learning algorithm.
产品评价对象的提取与分析的方法主要分为有监督的机器学习方法、半监督的机器学习算法、无监督的机器学习算法。
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