What is Automated Indexing?
Automated indexing is the process of assigning and arranging index terms without human intervention. The index is produced using algorithms, rulesets, or machine learning.
The world is continuously shifting from manual to automated practices. Government entities are following suit, paving way for automated acquisition, processing, and dissemination of information to the public. Automated indexing services is the solution to providing current, reliable, and accessible data to information seekers.
Manual vs Automated Indexing?
Some argue for the use of automated indexing because it is faster and more cost effective. This view is welcomed by many, because automated indexing can deal with the increasing amount of new material in various formats being produced that has made manual indexing slow and expensive. There is software such as Microsoft Word, Adobe Framemaker, and Extract that are capable of automatically indexing documents. These packages simplify and speed up the process by automatically reviewing documents and indexing information that is needed. Depending on the software, platforms such as Extract, can even index unstructured documents not only documents using predefined templates, because of their smart rulesets that are written to perform specifics tasks, and can scour entire documents and recognizing specific characters.
Why is Automated Indexing Great?
Faster and easier to produce. Relative to the process of producing an index manually. Automatically indexing an information source will save time and be faster, since most of the rigorous human effort would now be performed by a machine.
Easily modified. Automated indexing is easily retrievable, revisited, and modified when errors are noticed or due to future developments. This is an obvious advantage over manual indexing.
Transferability. Automated indexing permits government entities to share the information resources privately and publicly if available. An example of information that can be made public faster by using automated indexing would be Land Records.
Resources spend their time more effectively, validating or correcting questionable values only when needed, while letting the OCR engine perform the mundane task of document indexing.
Reduce overall resources needed, or can increase volume while maintaining resources.
Improves document indexing accuracy and allows users to focus on more valuable tasks.
Expedites entry of critical documents and data into your business transaction process.
Eliminates the burden of additional applications, databases, and duplicate configuration, to perform data extraction.
Improves customer service, by having data easily searchable and in certain instances, available to the public in a timely fashion.
About the Author: Tera Madigan
As a designer of experiences, Tera strives to bridge the gap between the user's needs, the physical world, and innovative technology by creating intuitive and engaging cross-channel experiences. By gaining valuable insight from people's motivations, behaviors, and attitudes, she enjoys analyzing findings to quickly iterate on ideas to help develop amazing products and experiences that meet real human needs--needs that they may never have thought about. She is an experienced Creative Leader who has a strong record of building and implementing successful branding, digital marketing, and eCommerce strategic plans. Tera has first-hand experience with starting and leading programs that have substantially increased awareness and driven large growth in eCommerce, UX, Web/App Design, and Digital Marketing for leading brands. She has a strong talent for understanding "the big picture" and leading large diversified and cross-functional teams in a large corporate setting as well as a fast paced, nimble and agile startup environment.