I happened to write an article not too long ago about the elimination of end user tagging, auto-classification and taxonomy tools. It appears that I struck quite a raw nerve, and was surprised that a gain of ruffians weren’t waiting for me outside my front door to silence my typing fingers forever. To clarify the issue, readers assumed that metadata generation and auto-classification tools would replace humans, which is not what I meant at all. My thoughts were to use the tools, and re-purpose that manpower to manage and improve the taxonomies, where a higher order of knowledge is required.
Our upcoming webinar, ‘Eliminating Manual Tagging at AllRegs by Ellie Mae, is a prime example of how metadata and auto-classification assist human efforts in managing content. AllRegs by Ellie Mae, will share their challenge and the solution during the webinar. For those who do not care to attend the webinar, AllRegs by Ellie Mae, had developed a content library spanning every aspect of the mortgage industry – literally hundreds of thousands of documents – rarely a day goes by without the majority of mortgage professionals visiting the AllRegs website. AllRegs is the definitive source for information, offering mortgage industry solutions for underwriting guidelines, FHA guidelines, mortgage training and education, federal and state compliance, policies and procedures, and more.
AllRegs by Ellie Mae sought to leverage advanced technology to continue to bring its customers a world-class library of mortgage lending research and reference content. The challenge was the tagging of content manually, by the internal publishers. As the volume of content continued to expand, the publishers were under time constraints and often documents were getting overlooked. As with all manual tagging, inconsistencies existed.
AllRegs by Ellie Mae selected conceptClassifier because of its ability to automatically generate compound term metadata, automatically classify it to one or more taxonomies, and has tight integration with FAST Search. The result was the elimination of end user tagging, which significantly reduced the workload for the publishing team, freeing them up to improve the classifications and manage and change the taxonomy. This delivered highly relevant and accurate information to their clients. For the end user, they no longer had to manually tag content, improving their productivity.
This is an excellent example of improving business processes through the addition of technology, and using resources to refine and improve the output.