Data Extraction for Deep Web Using WordNet

Hong, Jer Lang

doi:10.1109/tsmcc.2010.2089678

Cited by 27 publications

(16 citation statements)

References 27 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The drawbacks of grammar based approaches include huge amount of manual labor is required for writing extraction rules and also it requires domain expertise. In [17], a new approach for data extraction using lexical database WordNet has been proposed. Correct data rich region is determined by using WordNet.…”

Section: Related Workmentioning

confidence: 99%

Web Data Extraction from Scientific Publishers’ Website Using Heuristic Algorithm

Kumaresan¹,

Kalpana²

2017

IJISA

View full text Add to dashboard Cite

Abstract-WWW is a huge repository of information and the amount of information available on the web is growing day by day in an exponential manner. End users make use of search engines like Google, Yahoo, and Bingo etc. for retrieving information. Search engines use web crawlers or spiders which crawl through a sequence of web pages in order to locate the relevant pages and provide a set of links ordered by relevancy. Those indexed web pages are part of surface web. Getting data from deep web requires form submission and is not performed by search engines. Data analytics and data mining applications depend on data from deep web pages and automatic extraction of data from deep web is cumbersome due to diverse structure of web pages. In the proposed work, a heuristic algorithm for automatic navigation and information extraction from journal's home page has been devised. The algorithm is applied to many publishers website such as Nature, Elsevier, BMJ, Wiley etc. and the experimental results show that the heuristic technique provides promising results with respect to precision and recall values.

show abstract

Section: Related Workmentioning

confidence: 99%

Web Data Extraction from Scientific Publishers’ Website Using Heuristic Algorithm

Kumaresan¹,

Kalpana²

2017

IJISA

View full text Add to dashboard Cite

show abstract

“…In 2005, Zhai et al developed DEPTA [26] which uses tree matching to match the tree structures of data, assuming that data not only occur in repetitive order, but they also contain similar tree structures. Other approaches that use tree matching algorithms are such as NET [26] (using nested tree matching), WISH [13], [14], [15] (using tag counting). A variant of tree matching is developed in 2005, which uses primitive tandem repeat to match data with similar structures.…”

Section: Current Extraction Toolsmentioning

confidence: 99%

“…Due to the fact that ODE utilize ontology technique in its operation, it is the first wrapper which is able to extract single record data from the deep web, as this wrapper learn from its training data, and analyze the semantic properties of data instead of their patterns for data extraction. In 2011, Hong et al developed OW wrapper to extract and align data [14]. WordNet is used to analyze the semantic properties of data, where it checks for synonymous words and word disambiguation.…”

Section: Ontological Based Extractorsmentioning

confidence: 99%

Automated Data Extraction with Multiple Ontologies

Hong

2016

IJGDC

Self Cite

View full text Add to dashboard Cite

“…Jer Lang Hong in at al [7]The ontological technique could also reduce the number of potential data regions for data extraction and this was shorten the time and increase the accuracy in identifying the correct data region to be extracted. Measurement of the size of text and image to locate and extract the relevant data region further improves the precision of our wrapper.…”

Section: Related and Comparative Workmentioning

confidence: 99%

Knowledge base Construction using Hidden Web Retrieval Technique

Patel¹,

Ganatar²

2015

IJCA

View full text Add to dashboard Cite

Relations of algorithms for hidden web-focused information retrieval develop with it. When the stage the information retrieval, a huge difficulty arises and that is the information that one hidden web page can enclose manifold areas with extremely dissimilar information content. Hence the page has to be split into measurement and these parts examined separately for the results to be more precise. Web page segmentation and correlated technique have Therefore this paper suggests a combined approach that creates use of structural features and the visual features. It build a visual DOM tree on which the data records are recognized based on their structural similarity .The structure of these data records are reserved so that personage data items can be group effortlessly and precisely based on their visual features Which hidden web source do we intend at the information indispensable to access the data at the back web form and the type of interface. We proposed algorithm narrative vision based page segmentation (NVIPS) and also comparison DOM tree, VIPS.

show abstract

Data Extraction for Deep Web Using WordNet

Cited by 27 publications

References 27 publications

Web Data Extraction from Scientific Publishers’ Website Using Heuristic Algorithm

Web Data Extraction from Scientific Publishers’ Website Using Heuristic Algorithm

Automated Data Extraction with Multiple Ontologies

Knowledge base Construction using Hidden Web Retrieval Technique

Contact Info

Product

Resources

About