Lateral is a platform for reviewing and analyzing documents. It can be set up and used to augment different document analysis tasks, whether you need to find change-of-control clauses in a volume of contracts, or the methodology sections in a collection of reports. Lateral's machine learning algorithms can be trained in any language. Its key functionalities include:
Similar Content Recommendation: The recommendation API allows you to recommend similar documents to other documents or blocks of text. Relevance can be determined based on the text content of the document or optionally also based on user behaviour - hybrid recommender.
Tag Suggestion: The tag suggester learns to label documents with thematically relevant tags — words from a fixed, user-specified set. Therefore, when given a list of your existing tags the API can auto-tag new documents.
Clustering: Clustering groups your documents based on similarity so that you quickly get an overview of the main conceptual themes that your corpus contains.
Keyword Extraction: The keyword extractor returns a list of words whose meanings are similar to that of the input document, in descending order of relevance. The system does not need to train on labelled examples, since it uses the word vectoriser to find keywords.
