sparseness

This strategy can reduce the data sparseness and keep the search efficiency meanwhile .

这种优化策略可以在保证该算法数据查找效率不变的同时，进一步减少数据稀疏，提高空间利用率。

At the same time a new solution to the sparseness of training text is put forward .

同时对训练文本的稀疏问题提出了一种新的解决方案。

An improved active array errors calibration algorithm using the sparseness of mutual coupling matrix

一种利用互耦矩阵稀疏性的阵列误差有源校正改进算法

Spleen show cells sparseness at 1 month old .

脾脏1月龄细胞稀疏。

Experimental results show that Matrix filling method can effectively relieve the data sparseness problem in recommendation system .

实验结果表明：该方法可以有效缓解推荐中数据稀疏性问题。

But it also has many problems , such as data sparseness problem , the system scalability problem and time factor problem .

但协同过滤推荐算法还不够成熟，仍然存在一些问题，如数据稀疏性问题、系统的可扩展性问题和时间因素问题等。

With the increasing number of users and projects , sparseness problem will become more and more serious .

数据稀疏是影响推荐系统质量的瓶颈问题，随着用户和项目的数量不断增加，稀疏性问题将会越来越严重。

Sparseness Analysis of Radar Echoes and its Application in Ship and Chaff Discrimination

雷达回波稀疏性分析及其在舰船与箔条云鉴别中的应用

Sparseness of flow networks is revisited from the viewpoint of efficiency .

我们采用效率的观点，讨论了流网络的稀疏性问题。

Data sparseness led by the lack of training data restricts the promotion of the supervised methods .

由训练语料不足导致的数据稀疏问题限制了有指导方法的推广。

Sparseness discrete τ - p transform in poststack seismic trace extrapolation

基于稀疏离散τ-p变换的叠后地震道外推

The data sets have features such as high-dimensional , sparseness and binary value in many clustering applications .

在许多聚类应用中，数据对象是具有高维、稀疏、二元的特征。

Application of Combined Norm Constrained Sparseness Spike Inverse

L1-L2范数联合约束稀疏脉冲反演的应用

A genetic algorithm with adaptive evaluation function is presented to deal with data sparseness problem in automatic semantic tagging .

针对数据稀疏问题，采用适应度函数较灵活的遗传算法做语义的自动标注；

The calculation amount and local minimum are reduced taking advantage of sparseness of significant coefficients by wavelet transform .

利用多尺度之间的内在联系及小波域中重要系数的稀疏性，有效改进了局部极值、计算量等问题。

Based on the clustering method , the mixing matrix was first estimated by a new potential function using the sparseness of sources .

首先，利用变换后信源的稀疏特征，采用一新的势函数通过聚类算法估计混叠矩阵。

Incorporating external dictionary resource into event extraction task to solve the data sparseness problem in ACE corpus .

融入外部词典资源解决ACE语料数据稀疏问题。

In this paper , an improved algorithm of image feature extracting for independent component analysis was proposed based on basic functions'maximization of sparseness .

利用基函数稀疏性的极大值特点，本文提出一种改进的基于独立分量分析的图像特征提取算法。

This paper describes a method of extrapolating seismic traces based on the sparseness discrete τ - p transform .

这里研究的是一种基于稀疏离散τ-p变换的地震道缺失重建方法。

Wavelet-based Non-negative Matrix Factorization with Sparseness Constraints for Face Recognition

基于小波和非负稀疏矩阵分解的人脸识别方法

The scheme resolves the problem of high dimension and large sparseness in basket data and improves efficiency of clustering .

使用了一种新的事务表示法，解决了购物篮数据的高维性和稀疏性问题。并对算法进行了相应的改进，从而提高了聚类速度。

The current most widely used language model is statistical language model , and data sparseness is one of the main problems it has to face .

当前应用最广泛的语言模型是基于统计的语言模型。数据稀疏问题是统计语言模型所面临的主要问题之一。

Because the data it used was not users'rating but users'browse route , the problem of data sparseness and initial rating was resolved .

由于数据不是简单的用户评分，而是用户浏览网页的路径，这样就解决了数据稀疏问题和最初评价问题。

But traditional collaborative filtering algorithm has the shortcomings of sparseness , expansibility , and synonymy .

但传统的协同过滤算法存在着稀疏性、扩展性和同义性的问题。

NMFs can control sparseness explicitly and find parts-based representations for face images .

非负稀疏矩阵分解能显示地控制分解稀疏度和发现人脸图像的局部化表征；

Matrix filling method is a common way to solve the problem of data sparseness , while the effect of simple filling method is always not very good .

矩阵填充方法是解决稀疏性问题的常用方法，简单的填充方法效果往往不是很好。

The hierarchical clustering method is applied to deal with the problem that the solution of MLS-SVM is lack of sparseness .

运用谱系聚类方法解决多核最小二乘支持向量机的解缺乏稀疏性的问题。

In each group , the Bayesian inference is used for information sharing and one common sparseness hyper-parameters is discovered in each group .

在每个组内，可以进行信息共享并实施分层贝叶斯推理得出共享的超参数。

Compressive sensing is based on the sparseness of signals and the theory of sparse representation has also achieved significant progress in the past decade .

该理论建立在信号的稀疏性的基础之上，且信号稀疏表示理论在近十几年来也得到了长足的发展。

The experiments on several pattern classification problems show that HS-LSSVM has high sparseness while holds good classification performance and its sparse process is fast .

对多个分类问题的测试表明，HS-LSSVM具有稀疏率高，分类性能强，且稀疏化速度较快等优点。