Google sheds light on 'Dark Web' by searching scanned documents
Adds OCR technology so Google engine can index and search scanned PDF documents
Using optical character recognition (OCR) technology, Google's search engine now can convert scanned PDF documents into text that can be searched and indexed, the company said. Thus, government reports, academic papers and other scanned documents can now show up in search results. Search engines generally interpret PDF documents as images of text rather than text.
"While we've indexed documents saved as PDFs for some time now, scanned documents are a lot more difficult for a computer to read," Evin Levey, a Google product manager, wrote in a blog post. "To people reading these documents, the distinction between words and pictures of words makes little difference, but for a computer the picture is almost unintelligible. In the past, scanned documents were rarely included in search results as we couldn't be sure of their content. We had occasional clues from references to the document -- so you might get a search result with a title but no snippet highlighting your query."
This is part on an ongoing effort by Google to shed more light on the Deep, or Dark Web, where lies a massive amount of information that can be accessed but not indexed by a search engine because it is behind databases or in a format -- like PDF -- that can't be easily searched. In April, Google announced that it had started experimenting to find ways for its search engine to index HTML forms such as drop-down boxes or select menus that otherwise couldn't be found or indexed.
"In the past, Google would attempt to index these image files as well as possible, but could typically search only file titles and nearby metadata -- not the contents of the documents," he added. "From now on, Google searches will include the text within these scanned images in normal search results. Such technology has existed for quite a while, but accuracy has always been an issue -- and the fact that Google is doing it on such a massive scale makes it a very impressive accomplishment. It also opens the doors to much more thorough searching, especially for content that is often found in printed documents (like academic papers)."
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