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All Journal International Journal of Electrical and Computer Engineering TELKOMNIKA (Telecommunication Computing Electronics and Control) Indonesian Journal of Electrical Engineering and Computer Science
Ily Amalina Ahmad Sabri
Universiti Malaysia Terengganu
Computer Science & IT Electrical & Electronics Engineering

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A performance of comparative study for semi-structured web data extraction model Ily Amalina Ahmad Sabri; Mustafa Man
International Journal of Electrical and Computer Engineering (IJECE) Vol 9, No 6: December 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (663.643 KB) | DOI: 10.11591/ijece.v9i6.pp5463-5470

Abstract

The extraction of information from multi-sources of web is an essential yet complicated step for data analysis in multiple domains. In this paper, we present a data extraction model based on visual segmentation, DOM tree and JSON approach which is known as Wrapper Extraction of Image using DOM and JSON (WEIDJ) for extracting semi-structured data from biodiversity web. The large number of information from multiple sources of web which is image’s information will be extracted using three different approach; Document Object Model (DOM), Wrapper image using Hybrid DOM and JSON (WHDJ) and Wrapper Extraction of Image using DOM and JSON (WEIDJ). Experiments were conducted on several biodiversity website. The experiment results show that WEIDJ approach promising results with respect to time analysis values. WEIDJ wrapper has successfully extracted greater than 100 images of data from the multi-source web biodiversity of over 15 different websites.
WEIDJ: Development of a new algorithm for semi-structured web data extraction Ily Amalina Ahmad Sabri; Mustafa Man
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 19, No 1: February 2021
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v19i1.16205

Abstract

In the era of industrial digitalization, people are increasingly investing in solutions that allow their process for data collection, data analysis and performance improvement. In this paper, advancing web scale knowledge extraction and alignment by integrating few sources by exploring different methods of aggregation and attention is considered in order focusing on image information. The main aim of data extraction with regards to semi-structured data is to retrieve beneficial information from the web. The data from web also known as deep web is retrievable but it requires request through form submission because it cannot be performed by any search engines. As the HTML documents start to grow larger, it has been found that the process of data extraction has been plagued with lengthy processing time. In this research work, we propose an improved model namely wrapper extraction of image using document object model (DOM) and JavaScript object notation data (JSON) (WEIDJ) in response to the promising results of mining in a higher volume of image from a various type of format. To observe the efficiency of WEIDJ, we compare the performance of data extraction by different level of page extraction with VIBS, MDR, DEPTA and VIDE. It has yielded the best results in Precision with 100, Recall with 97.93103 and F-measure with 98.9547.
A deep web data extraction model for web mining: a review Ily Amalina Ahmad Sabri; Mustafa Man
Indonesian Journal of Electrical Engineering and Computer Science Vol 23, No 1: July 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v23.i1.pp519-528

Abstract

The World Wide Web has become a large pool of information. Extracting structured data from a published web pages has drawn attention in the last decade. The process of web data extraction (WDE) has many challenges, dueto variety of web data and the unstructured data from hypertext mark up language (HTML) files. The aim of this paper is to provide a comprehensive overview of current web data extraction techniques, in termsof extracted quality data. This paper focuses on study for data extraction using wrapper approaches and compares each other to identify the best approach to extract data from online sites. To observe the efficiency of the proposed model, we compare the performance of data extraction by single web page extraction with different models such as document object model (DOM), wrapper using hybrid dom and json (WHDJ), wrapper extraction of image using DOM and JSON (WEIDJ) and WEIDJ (no-rules). Finally, the experimentations proved that WEIDJ can extract data fastest and low time consuming compared to other proposed method. 
Improving Performance of DOM in Semi-structured Data Extraction using WEIDJ Model Ily Amalina Ahmad Sabri; Mustafa Man
Indonesian Journal of Electrical Engineering and Computer Science Vol 9, No 3: March 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v9.i3.pp752-763

Abstract

Web data extraction is the process of extracting user required information from web page. The information consists of semi-structured data not in structured format. The extraction data involves the web documents in html format. Nowadays, most people uses web data extractors because the extraction involve large information which makes the process of manual information extraction takes time and complicated. We present in this paper WEIDJ approach to extract images from the web, whose goal is to harvest images as object from template-based html pages. The WEIDJ (Web Extraction Image using DOM (Document Object Model) and JSON (JavaScript Object Notation)) applies DOM theory in order to build the structure and JSON as environment of programming. The extraction process leverages both the input of web address and the structure of extraction. Then, WEIDJ splits DOM tree into small subtrees and applies searching algorithm by visual blocks for each web page to find images. Our approach focus on three level of extraction; single web page, multiple web page and the whole web page. Extensive experiments on several biodiversity web pages has been done to show the comparison time performance between image extraction using DOM, JSON and WEIDJ for single web page. The experimental results advocate via our model, WEIDJ image extraction can be done fast and effectively.
Co-Authors Mustafa Man