Obedience School for Cross Domain Semantics
July 2, 2012
It is possible to teach an old dog new tricks according to Semanticweb.com’s article, ‘FirstRain Spotlights Semantics Across Domains’. Semantic approaches for a targeted domain work well because one can train the NLP engine to recognize key words that are applied. The downside is that the business world of today is vast and the current training limitations for specific domains cannot always scale.
FirstRain has opened a unique version of a semantic obedience school as:
“Affinity scoring must be a breakthrough for classes of information where there is a lot of ambiguity, and the cool thing about it is that you can actually apply it in a way to create a virtuous self-improving spiral that works across massively different information domains. When you set up the correct feedback loop of affinity scoring and don’t encode to different domains, but let it swing across those you are trying to match things to, you can create a self-learning system.”
The new system derived by FirstRain is capable of re-training the most stubborn of semantics and inspiring functionality. By creating adaptable semantics they have taught an already workable system to handle a variety of information in an even more efficient process. The semantic obedience school could very well be the next big thing in the business world if all goes as they plan. The new routine seems feasible, so has FirstRain cracked the tough training nut of cross domain semantics?
Jennifer Shockley, Juuly 2, 2012
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