大侠，帮忙翻译一段文字！！！

Question

在信息技术飞速发展的今天，文本是我们获取信息的主要来源。然而面对海量、异构的文本信息人们往往的显的束手无策。因此，寻找一种行之有效的文本聚类算法已成为一个重要的研究课题。
本文深入研究了几种常用的聚类方法和几种文本数学模型的构建，重点研究了K均值算法及其在文本聚类中的扩展算法—超球K均值算法(SKM算法)。该算法用Salton教授提出的向量空间模型把文本表示成不可视的超球向量空间的一个向量，采用一定的预处理手段(降维、同义词归并、停用词过滤)完成维数约减，使用余弦相似度度量文本之间的相似度，并选择总凝聚度作为目标收敛函数，通过有限次的迭代达到局部最优，输出聚类结果。实验结果验证了SKM算法的有效性和可行性，进一步表明SKM算法简单、高效，十分适合文本挖掘。

Answer 1

In today's world where the information technology develops at a crazy speed,text is the main source of the information that we get.However,people often shrivel at the sight of mountains of text information.Thus,it has become an increasingly important task to find an effective text clustering method.
This article discusses in-depth several conventional text clustering methods and the construction of several mathematical models of text,and explores in particular the K average value method and its expanded use in text clustering--the SKM method.This method uses what Professor Salton has proposed as the vector spacial model to express text as an invisible vector in hyperspherical space.It makes use of certain pre-disposal methods (reduce the dimensions,clustering thesaurus,filtering out old-fashioned words) to reduce the dimensions.It uses cosines to measure the degree of similarity between texts and uses the total similarity as the target convergence vector.It produces clustered results by using restricted iteratives to achieve partial perfection. Experiments have shown that the SKM method is both feasible and executable ,and further proven that SKM method is simple,effective,and suitable for text mining.

呼……好长，全是自己翻译的，有些术语可能翻译的不太准确，但大意是没错的，希望能够帮到你。

Answer 2

第一段翻译如下
Today developing at full speed in IT, main part being that we gain information stems from a version. But version information people who faces great capacity for liquor , the isomerism sometimes obvious no way out. Therefore, seek one kind of effective version cluster-algorithm already becoming a important go into problem.
第二段翻译如下
The structure going deep into the mathematic model having studied several kinds clustering method and several kinds versions in common use builds the main body of a book , priority the algorithm having studied K mean value and their expansion algorithm in version clustering surpasses the ball K mean value algorithm (SKM algorithm). A vector owing an algorithm the ball vector space a version is expressed with vector space model brought forward by Salton professor becoming being over being not allowed to look at, adopt certain pretreatment means (conquer the thinking , synonym conflation , stop verbal fliteration) to accomplish a dimension cutting about , uses the similarity degree between degree of amounts cosine similarity versions , chooses general coacervation degree and restraining self's a function as the target, result optimum , exporting clustering by the fact that inferior limited iteration reaches part. The experiment bear fruit has verified algorithmic validity of SKM and feasibility , has indicated the SKM algorithm simplicity further, high-effect, the version very suitable excavates.

文章有些长、、望认真看完、、标准人工翻译、、希望可以帮助你、、

Answer 3

楼主，我建议你下回专门找那些英语好的人翻，否则有的人用机器翻译来应付你，你能分辨得出来吗？ 即使能的话，岂不还是浪费时间。。。 好多人都是站内找我直接给他们翻译。。。。

Answer 4

In modern time of rapid development of information technology,text is the main source for us to acquire information.But people always seem to be at loss when they face mass and heterogeneous text information.So it has become an important subject of study to find an effective text clustering algorithm.
This article deeply studies several common clustering method and several constructions of text mathematics model and focuses on the study of K mean algorithm and its extended algorithm in text clustering - SKM algorithm.This algorithm expresses text as a vector of invisible super-ball vector space according to the vector space model by professor Salton.It uses some pre-processing methods(dimension reduction,synonym merging,obsolete words filtering) to accomplish dimension reduction and uses cosine similarity to measure the similarity of text.It also selects total clustering degree as objective convergent function,reaches partial optimization through limited iterations, and outputs clustering results.Experimental results prove the effectiveness and feasibility of SKM algorithm and further demonstrates it's simple,efficient and suitable for text mining.

Answer 5

today that technology developing fast,text is the mainly source for get the information....
（我英语果然是不行。。。。。。。。。。。。TOT）

Answer 6

In the rapid development of information technology, the text is our today's main source of information. But in front of the text messages, heterogeneous mass of people tend to show the helpless. Therefore, a kind of effective text clustering algorithm has become an important research topic.
This paper studies several common clustering method and mathematical model building several text studied in the text and k-means clustering algorithm of extension algorithm k-means algorithm (super ball SKM algorithm). This algorithm is put forward by professor Salton vector space model of the text representation of a treat of ball of vector space, using a vector of pretreatment methods (dimension reduction, synonyms merging, stop words filter) complete dimension reduction, using cosine about similarity between text and choose the similarity degree of total condensed as the objective function, the convergence of iterative times by limited to local optimal, output clustering results. Experimental results verify the feasibility and effectiveness of the algorithm SKM and further shows SKM algorithm is simple, efficient, very suitable for text mining.

绝对正确