Sentiment feature: Detect positive, negative, and neutral
Use Sentiment to learn about concepts’ association with types of emotion. Daylight uses a proprietary deep learning model to determine sentiment for all concepts in a project and assigns a label of positive, negative, or neutral, based on the concept’s context. Please use the percentage counts in this feature as a general indication.
Volume feature: Quantify concepts
Gain quick insight into concept representation across the dataset. The Volume feature automatically quantifies how frequently concepts are referenced in the project using the exact and conceptual matching identified by QuickLearn.
Start with the Highlights feature
The Highlights feature is a starting point in understanding the contents of your project. In this feature, orient yourself and start navigating the primary questions you can answer using Daylight: You’ll first view Daylight’s answers to these questions in Highlights, and then engage deeply with each data perspective as you move through the Volume, Sentiment, Drivers, and Galaxy features. What metadata do my documents have? — View the […]
Daylight
The Luminoso product that analyzes natural language text documents and produces insights about those documents. Daylight uses Luminoso QuickLearn technology to learn specific meanings of words and phrases in a dataset. Daylight identifies concepts that are most meaningful within a project and its conceptual matches.
Compass
The Luminoso product that automatically analyzes text samples as they arrive in real time and classifies them based on user-provided labeled examples or defined topics.
QuickLearn
The transfer learning technology that Luminoso uses to learn from unstructured natural language text samples. QuickLearn combines a background space trained on ConceptNet and a variety of freely available text and domain text. QuickLearn then integrates the text documents that you want to analyze and creates a new space of word embeddings specifically tuned to […]
Highlights
The Daylight feature where you can quickly view high-level insights about your project. Use Highlights to orient yourself to your project and start navigating the questions you can answer using Daylight.
Volume
Use Daylight’s Sentiment feature to evaluate whether concepts are positive, negative, or neutral based on their context. Using deep learning, Sentiment offers you a highly granular view into how users really feel about your services and offerings.
Sentiment
Use Daylight’s Sentiment feature to evaluate whether concepts are positive, negative, or neutral based on their context. Using deep learning, Sentiment offers you a highly granular view into how users really feel about your services and offerings.
Drivers
Find terms that are prevalent and reveal a significant impact on a measurable aspect of your data in Daylight’s Drivers feature. For example, in a restaurant review project where “scores” are star ratings, the concept “long line” might be a negative driver. A driver’s impact represents the difference between the average score for all documents […]