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robot metadata

On Automating Metadata Extraction for Academic Publishing

In Guest Contributors by Guest ContributorNovember 9, 2015

JET SourceHOV

SourceHOV argues that artificial intelligence can obviate the need for publishers to manually create metadata tags and significantly streamline workflows.

By Gary Rodrigues, SourceHOV

We believe that AI is a game changing technology that will revolutionize the way robot metadatapublishers manage their content. Machine learning technology is at a point where it can deliver significant value and, for example, obviate the need for publishers to manually identify, tag and convert academic journal front matter from author manuscripts. The obvious advantage other than significant cost savings is that publishers are able to rapidly publish their metadata to their partners.

What we are witnessing is the realization that speed to market will become a critical component as they strive to monetize their content. The use of AI to enrich the content will give them the balance of speed to market and quality associated with their brand.

SourceHOV is pioneering the use of this technology in publishing and last month launched two new products that will help publishers speed up content generation, make more use of existing content, and consolidate large content base through the use of machine learning, natural language processing, OCR and classification technology, combined with adaptive workflow.

The first of these is known as JET, which is an automated metadata extraction platform for academic publishers. By applying machine learning, natural language processing, and mathematical modeling to content, manual intervention is completely removed. This provides immense speed for the publisher to go to market and does away with vendor dependency. The results are time, cost, and quality benefits.

Machine learning, natural language processing, and mathematical modeling are crucial for anyone publishing content and wanting to utilize it fully. Every publisher must accurately identify various essential elements in their content in order to utilize it. The question is how to do so without incurring the time, cost, and accuracy issues of manual intervention. More publishers are now recognizing the great benefits of automating this process and are clamoring for a solution. Our solution for these publishers is JET.

BoxOffice SourceHOV

The second product, BoxOffice, provides a range of cloud-based enterprise information management services that enable organizations to ingest, extract, and store key data from documents. “It empowers business units with actionable and trackable intelligence,” says Nakul Parashar, VP for Enterprise Content Management, adding that “cloud-based BoxOffice offers greater security, a drastic reduction in paper handling, and allows role-based access for seamless retrieval in most formats.”

Publishers as clients have always been looking at reducing costs, but for most, cost reductions have now become critical to survival. Publishers are looking at achieving high quality, better project management, and faster turnaround times at much lower costs, which are all major challenges to solutions providers like us. They also want to repurpose their content. At SourceHOV, we took these challenges as our guiding spirit to achieve our objective, which is to help publishers.

Gary Rodrigues is director of business development at SourceHOV.

About the Author

Guest Contributor

Guest contributors to Publishing Perspectives have diverse backgrounds in publishing, media and technology. They live across the globe and bring unique, first-hand experience to their writing.

Tags: Academic Publishing, Artificial Intelligence, Metadata, SourceHOV, United States, workflow

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