Search Results for "document"

...The goal of text classification is to assign documents (such as emails, posts, text messages, product reviews, etc...) to one or multiple categories. Such categories can be review scores, spam v.s. non-spam, or the language in which the document was typed. Nowadays, the dominant approach to build such classifiers is machine learning, that is learning classification rules from examples. In order to build such classifiers, we need labeled data, which consists of documents and their corresponding categories (or tags, or labels).

...Unlike database fields, which are easily queried, text contains unstructured data that must be parsed for key objects that can be transformed in to powerful metrics. Litersta - textual analytics - software leverages statistical algorithms to programmatically locate, and extract, overall document sentiment, word frequencies, and document similarities. The Litersta web application runs locally on your server - behind your firewall. This strategy keeps your data confidential and secure.