In a world of data overload, Grapeshot offers WordRank™ technology to navigate the spectrum of choice, using words and phrases we all learn from childhood.
Grapeshot’s Signal™ weights words and phrases in real-time to identify the significant signal in any document. These weights change as the world of big data pulses and changes by the second too. Grapeshot’s adaptive machine learning algorithms within WordRank™ power automated page classification system, where customers can easily invent new segments of choice and get instant feedback on the value of words, phrases and segments for additional consumer insights.
WordRank™ has sophisticated feedback loops and “learns” as it runs, based on algorithms first pioneered at Cambridge University and latterly productionized by Dr. Porter, the creator of the Porter Stemmer.
Grapeshot uses a probabilistic algorithmic approach. All words and phrases in any digital content is profiled for real-time weights which determine their relative contribution to a contextual match. If new words or phrases appear in the big data collections or in the custom designed segments, then the weights adapt and change accordingly.
Weighted words help identify the most relevant sentences in pages, significant fields within structured data, and equips fast, scalable segmentation. Most importantly any data object can auto-discover other media assets with overlapping WordRank™ weighted word profiles – allowing easy traversing across data of different formats, in different data silos.
WordRank™ unlocks the flexibility and simplicity for marketers to combine data into shared insights for understanding consumer activities in real-time or trends over time, all interpreted with the simplicity of words and phrases which all people can understand and action.