Schmidt and his colleagues created an algorithm that can make an annotated web page for the Australian Museum freely accessible to the world at no cost. After collecting millions of web pages (with embedded metadata that includes keywords for each of a collection's pages) -- the amount is estimated to be in the hundreds of millions of entries -- the researchers compiled the lists of keywords that were used in these collections. To make such a list of metadata free for others to use, they used a form of automated text processing called “semantic extraction.” Using one of the researchers' custom-written statistical software for this purpose, they began comparing the number of unique keywords in each of the collections' entries with the number of times each word appeared on a webpage from the Australian Museum. The researchers then applied a set of rules to their results based on their knowledge of what words are most commonly used to produce the results -- the more common words appear most often in the web pages and the more likely they are to appear in the metadata of those pages. The researchers then used those rules to build an automatic web browser to match the web pages against the collection of keywords. They also added special code that allowed the browser to automatically check documents against the metadata. When the automatic program matched and found a match for a document, it would use data on the web page's “ID,” title, and URL to generate a URL. It would then link the document to the metadata file, and in turn, that record of that page's URL would be used to create a link to that record in the collection's metadata file.
“After collecting millions of web pages (with embedded metadata that includes keywords for each of a collection's pages) -- the amount is estimated to be in the hundreds of millions of entries -- the researchers compiled the lists of keywords that were used in these collections. To make such a list of metadata free for others to use, they used a form of automated text processing called “semantic extraction.” Using one of the researchers' custom-written statistical software for this purpose, they began comparing the number of unique keywords in each of the collections' entries with the number of times each word appeared on a webpage from the Australian Museum.
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Literary and Linguistic Computing Advance Access published April 16, 2010, The inadequacy of embedded markup for cultural heritage texts ............................................................................................................................................................
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