Using AI - driven unstructured data analysis such as
via natural language processing (NLP) to better understand law firm invoices has become a significant field all to itself.
We differentiated between computational approaches (either based on volume data, such as the number of mentions related to a party or candidate or the occurrence of particular hashtags; or endorsement data, such as the number of Twitter followers, Facebook friends or the number of «likes» received on Facebook walls), sentiment analysis approaches, that pay attention to the language and try to attach a qualitative meaning to the comments (posts, tweets) published by social media users employing automated tools for sentiment analysis (i.e.,
via natural language processing models or the employment of pre-defined ontological dictionaries), and finally what we call supervised and aggregated sentiment analysis (SASA), that is, techniques that exploit the human codification in their process and focus on the estimation of the aggregated distribution of the opinions, rather than on individual classification of each single text (Ceron et al. 2016).
Not exact matches
Orcadex is a business intelligence platform focused on the blockchain and cryptocurrency verticals, collecting data
via machine learning and
natural language processing to offer analysis and insights to customers.
DataNovo enables law firms and legal practitioners to capitalize on cost and time - saving strategies by providing synthetic legal expert prior art search results
via DataNovo's
natural language processing of documents, with machine learning and data mining techniques to give you expert results at minimal cost and time.
Her intelligence comes
via Bing, which has access to Tellme's
natural language processing (which Microsoft acquired in 2007), the Satori knowledge repository and Microsoft's enormous cloud
processing power.