Extract the maximum amount of information when analysing immense data sets.
Analyse data, classify topics, update taxonomies, extract brand mentions
Entity Extraction & Classification
Give data analysts the power to focus only on information that’s relevant to them. Simplify the process of investigating datasets, by identifying crucial elements within unstructured databases. With entity extraction, also known as named entity recognition, we can identify crucial elements of the text and classify them. That makes unstructured data readable and usable for processing.
Оrganize and tag content into categories such as topics, types of industries, or countries of origin. We can use multi-label tagging on both structured and unstructured data, which will help you get the best out of your information. Further, we can apply the taxonomy to millions of articles to ensure we don’t miss any crucial details.
Extract and analyze the tone of a text or the public from an unstructured document. Usually, we look at whether the overall sentiment is negative, neutral, or positive. In some cases, we also discover other emotions of the author or comments such as anger, disgust, or liking.
Increase time spent on page through relevant content recommendations. Our system provides personalized content recommendations to your readers. We do it through similarity clustering and keyword identification by combining text mining technologies with human experience.
Team & capacity
Benefit from supervised and unsupervised content enrichment.
Supervised content enrichment
- General Sentiment – classify positive to negative emotions in social media conversations, blogs, forums, and other forms of unstructured web text.
- General Taxonomy – classify content in a wide set of categories.
- Name Entity Extraction (NER) – automatically find mentions of people, organizations, brands, locations, events, and others.
Unsupervised content enrichment
- Similarity Clustering – identify relevant keywords in an article and cluster similar articles based on their frequency.
- Anomaly detection – detect anomalies and any discrepancies in texts based on historical data comparison. Automatic detection can be used in media monitoring services to identify peaks of certain topics and detect what people talk about the most.
Team & capacity
We can tailor our supervised content enrichment services to your needs. Our tailored supervised techniques use the technologies in the default content enrichment, entirely customized to your organization’s requirements.