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.
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.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.