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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Pui Leng Goh Jer Lang Hong Ee Xion Tan Wei Wei Goh |
| Copyright Year | 2012 |
| Description | Author affiliation: School of Computing and IT, Taylor's University, Malaysia (Pui Leng Goh; Jer Lang Hong; Ee Xion Tan; Wei Wei Goh) |
| Abstract | Wrappers are tools used to extract relevant information from HTML pages. Current approaches use DOM tree, visual cue, and ontology to extract data. DOM tree based techniques are fast and simple. However, they are not as accurate as visual based wrappers due to lack of additional information needed to perform data extraction. Visual based wrappers, on the other hand, are slow due to the extra processing needed to obtain visual cue from the underlying browser rendering engine. Ontology based wrappers are accurate, but they are also slow and need manual tuning to operate them. In this paper, we propose a novel visual based wrapper to extract information from HTML pages. Our wrapper uses visual cue to eliminate unnecessary regions, hence reduces the running time of extraction task as our wrapper only needs to consider the relevant region for extraction. Then, our wrapper removes irrelevant data from the relevant region using visual cue. Experiment results show that our wrapper outperforms state-of-the-art wrapper WISH in data extraction. |
| Starting Page | 1196 |
| Ending Page | 1200 |
| File Size | 338621 |
| Page Count | 5 |
| File Format | |
| ISBN | 9781467300254 |
| e-ISBN | 9781467300247 |
| DOI | 10.1109/FSKD.2012.6233750 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2012-05-29 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Visualization Search Engines Automatic Wrapper Search engines Ontologies Deep Web HTML Data mining Web sites Engines |
| Content Type | Text |
| Resource Type | Article |
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