So often when searching a database, records in the search results include links to PDFs and other electronic documents. Somewhere in the linked documents are pages with information related to the search, but where? And which pages are the most relevant? A user can use their PDF reader’s Find function to search again for keywords in the document, but that’s repetitive and not especially sophisticated. What if there was a better way of reviewing content within linked documents?
The Andornot Embedded Document Viewer breaks every PDF or similar document down into individual pages, with OCRd, indexed, searchable full text content available to searchers. When a user searches a database, the search results can include individual pages of linked documents, with their search terms highlighted, and with the most relevant pages shown, not just the record that links to the resource.
The screenshot below shows search terms highlighted on page. Additional images and examples are available here.
By viewing individual pages, rather than having to open and review each linked document in its entirety, a user can more quickly assess resources.
Other features include the ability to navigation through the document, zoom in and out of a page, and view thumbnails of all pages.
The Andornot Embedded Document Viewer is often added to the Andornot Discovery Interface search engine. Search results can represent the individual pages of a document that best match the user's search, ranked by relevancy, rather than just the catalogue or parent metadata record for the entire document.
The Andornot Embedded Document viewer is incorporated into the following projects, which are also based on the Andornot Discovery Interface:
Contact us for more information about enhancing search and discovery of linked, digitized resources.