HTML 221 184 0 11 1.0000 0.9521 0.9752 97.35
PURE 8 403 0 5 1.0000 0.6153 0.7611 98.79
RSS 139 261 11 5 0.9261 0.9651 0.9450 96.15
Avg 0.8731 97.35%
Corresponding graph has been plotted for obtained F-Measure and Accuracy as shown in Fig. 5.
Fig. 5 Accuracy analysis for 60:40
4.1.3. Results obtained from 50:50 Dataset
In Table 3, we observe that 50% of the data is considered as training set and the rest 50% is used as testing data. With this set of data we have achieved an average accuracy of 97.36% and an F-measure of 0.8031.
Table 3 Results obtained for 50:50dataset
XML
URLs True
Positive True
Negative False
Positive False
Negative Precision Recall F-Measure Accuracy
CODE 29 485 11 4 0.7250 0.8780 0.7940 97.16
HTML 290 228 0 11 1.0000 0.9630 0.9810 97.91
PURE 6 510 2 11 0.7500 0.3520 0.4812 97.50
RSS 184 329 11 5 0.9430 0.9730 0.9580 96.91
Avg 0.8031 97.36%
Corresponding graph has been plotted for obtained F-Measure and Accuracy as show in Fig. 6.
Fig. 6 Accuracy analysis for 50:50
5. Conclusion
We have presented a brief overview of importance of classification and its advantages. To achieve the classification system, we proposed four successive Algorithms to create knowledge base. After performing all the four consecutive Algorithms on testing data set elements, matching has been done. Based on the highest matching score Web pages are classified into their respective classes. After proposing an Algorithm, we have conducted extensive experimentation on various ratio of data set and compared the obtained F-Measure and Accuracy score with each other. Overall we have achieved average accuracy of 96.99% classification with very less error rate.
B.原文的翻译
Web数据挖掘的应用方向中基于语义结构的
XML的URL分类
如今，我们都知道网络是新兴的研究领域。例如，通过分析可用性测试提高网页的质量，在小屏幕上浏览网页服务就像手机、PDA（个人数字助理）等产品的网页信息中提取数据，通过这些数据跟踪用户评论和意见。一般来说，我们称之为Web挖掘。根据分析目标可以将Web挖掘分为三种不同类型，即Web使用挖掘、Web结构挖掘和Web内容挖掘。
WWW（World Wide Web）财团表示，HTML有很多弊端，如有限的定义的标签，不区分大小写，半结构化的设计只能显示有限的选项数据。后来为了克服这些困难，一些技术已被引入，如XML，Flash等。因此，Web开发人员开始迁移去开发网页，为这些新兴的网络技术提供一个更好的描述网页内容的语义结构。因此，现在我们可以看到更多的网页在网站的开发之中利用XML和Flash技术。论文网 Web数据挖掘的应用英文文献和中文翻译(4):http://www.youerw.com/fanyi/lunwen_38929.html