Earticle

초록

영어

Recent advancement in Internet Technologies has made web browsing increasingly easy and user friendly. From the traditional method of desktop web browsing and the birth of dial up modem connection, users nowadays are able to enjoy a fast and reliable web browsing via high speed wireless Internet connection and portable mobile devices. Browsing a web has become much easier with the state of the art search engines such as Google, which provide much functionalities which could make browsing easier such as improved crawler, easy to use search interface, web personlization, Web 3.0 support and integration and many more. In order to build a robust and reliable search engine, the developer needs to integrate all the data and present them in a meaningful format for user’s viewing convenience. Integrating these data is a tedious task as data usually occur in numerous format, and layout. Furthermore, web developers usually present the data content in various languages of their choice, which made the processing of these data increasingly difficult. There is also no standard convention to represent the data format and even a standardize rule to process this data has not been developed. To resolve this issue, researchers develop data extractor which could effectively extract data from web sources, tabulate them, and used it for further processing. However, not all data are correctly extracted, they may either missed certain valuable information or contain additional unnecessary information. In the case of unnecessary information, researchers use a cleaning method to remove them such that the data extracted are free of errors. Removing these data is important as unnecessary information may affect the accuracy of subsequent extractor tools, hence may eventually prevent the tool from performing its task efficiently. In this research proposal, we embark on a data cleaning tool to clean data using ontology tools. Experimental results show that our tool is highly efficient in data cleaning and is able to outperform existing state of the art tools.

목차

Abstract
 1. Introduction
 2. Related Work
 3. Problem Formulation
 4. Motivation
 5. Proposed Solution
  5.1. Initial Stage
  5.2. Template Identification
  5.3. First Stage Cleaning
  5.4. Second Stage Cleaning
  5.5. Third Stage Cleaning
  5.6. Fourth Stage Cleaning
  5.7. Fifth Stage Cleaning
  5.8. Data Cleaning Finalization
 6. Experimental Tests
 7. Conclusions
 References

키워드

저자

• Jing Ting Wong [ School of Computing and IT, Taylor’s University ]
• Jer Lang Hong [ School of Computing and IT, Taylor’s University ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Grid and Distributed Computing

• 간기

  격월간

• pISSN

  2005-4262

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605