Within artificial intelligence (AI) there are a number of different technologies and they lie at different points in the curve of adoption with virtual assistants and robo-advisors being the most common. Semantic technologies have a world of discovery lying ahead. Although it is widely used as the underlying technology for most deep learning systems, there is a vast amount of work remaining in this area and experts believe it is far from being an exhausted technology.
Semantic fingerprinting and semantic technologies are about extracting meaningful data from quantitative data, text, voice, video and images. In publishing, this means tagging documents with metadata to identify the author name, institution, subject matter, or any relevant piece of information. This is like merging all of those card catalogs into a single databank, accessible all at once.
In academic publishing, the benefit of this fingerprinting is pretty clear. Knowing the author’s name, date of birth, institution, or really anything you want allows him or her to be identified quickly and, more importantly, with accuracy.
And while we talk about academic publishing a lot around these parts, the private sector can get just as much use out of semantic fingerprinting as the public. Researchers in finance and adjacent fields have increasingly been working with textual data, a common challenge being analyzing the content of a text. Traditionally, this task has been approached through labor- and computation-intensive work with lists of words. With semantic fingerprinting, we compare word list analysis with an easy-to-implement and computationally efficient alternative. Semantic fingerprinting significantly reduces the barrier to entry for research involving textual content analysis.
Access Innovations, Inc. offers the Semantic Fingerprinting Web service extension as part of their Data Harmony software. Semantic Fingerprinting is a managed Web service offered to scholarly publishers to disambiguate author names and affiliations by leveraging semantic metadata within an existing publishing pipeline.
The Semantic Fingerprinting Web service data mines a publisher’s document collection to build a database of named authors and affiliated institutions, and then expands the database over time with customization and administration services provided by Access Innovations during configuration. The author/affiliation database powers M.A.I.™ (Machine Aided Indexer) algorithms for matching names in new content received from contributors. During the configuration phase, an essential component is the graphical user interface (GUI) where users disambiguate unmatched names using clues that M.A.I. surfaces as a result of rigorous document analysis.
Melody K. Smith
Sponsored by Access Innovations, the world leader in taxonomies, metadata, and semantic enrichment to make your content findable.
