Automatic Identification of Specific Web Documents by Using Centroid Technique
نویسندگان
چکیده
In order to reduce time to find specific information from high volume of information on the Web, this paper proposes the implementation of an automatic identification of specific Web documents by using centroid technique. The Initial training sets in this experiment are 4113 Thai e-Commerce Web documents. After training process, the system gets a Centroid e-Commerce vector. In order to evaluate the system, six test sets were taken under consideration. In each test set has 100 Web pages both known e-Commerce and non eCommerce Web pages. The average system performance is about 90 %.
منابع مشابه
A survey on Automatic Text Summarization
Text summarization endeavors to produce a summary version of a text, while maintaining the original ideas. The textual content on the web, in particular, is growing at an exponential rate. The ability to decipher through such massive amount of data, in order to extract the useful information, is a major undertaking and requires an automatic mechanism to aid with the extant repository of informa...
متن کاملA Technique for Improving Web Mining using Enhanced Genetic Algorithm
World Wide Web is growing at a very fast pace and makes a lot of information available to the public. Search engines used conventional methods to retrieve information on the Web; however, the search results of these engines are still able to be refined and their accuracy is not high enough. One of the methods for web mining is evolutionary algorithms which search according to the user interests...
متن کاملModeling A Generic Web Classification System Using Design Patterns
In order to save time in extracting specific information from high volume of data in web documents, this paper proposes an architectural model of generic web document classification system using design patterns for classifying web documents. This work implements two classification techniques for classifying Thai web documents, namely centroid classification and neural network classification, ba...
متن کاملAutomatic Document Topic Identification Using Hierarchical Ontology Extracted from Human Background Knowledge
The rapid growth in the number of documents available to end users from around the world has led to a greatly-increased need for machine understanding of their topics, as well as for automatic grouping of related documents. This constitutes one of the main current challenges in text mining. In this work, a novel technique is proposed, to automatically construct a background knowledge structure ...
متن کاملPerson Name Identification in Chinese Documents Using Finite State Automata
This research is about automatic identification and extraction of person names in Chinese text documents. Solutions to this problem have immediate and extensive applications in many areas especially in Web Intelligent Agents related applications such as Web search engines, Web data mining, and automatic Web information analysis. We have noted that while finite state automata (FSA) based techniq...
متن کامل