An analysis engine in the text analytics industry is defined as a software component that performs some type of linguistic analysis on natural language text. This can include tasks such as part-of-speech tagging, named entity recognition, or sentiment analysis.
The term “analysis engine” is also used outside of the text analytics industry, typically to refer to a software component that performs some sort of data analysis. For example, in the business intelligence field, an analysis engine might be used to perform financial forecasting or marketing mix modeling.
It’s important to note that the term “analysis engine” is used quite differently within different industries. When reading about this term, it’s crucial to pay attention to the context in which it is being used.
Procedure of analysis engine
The analysis engine is a process or set of processes that extract meaning from text data sources in order to generate insights that can be used to improve decision making
There are four main types of analysis engines:
1. Linguistic Analysis Engines: These analyze text data using Natural Language Processing (NLP) techniques in order to extract some sort of linguistic insight. For example, a part-of-speech tagger would be a type of linguistic analysis engine.
2. Statistical Analysis Engines: These analyze text data using statistical methods in order to extract some sort of quantitative insight. For example, a word count tool would be a type of statistical analysis engine.
3. Machine Learning Analysis Engines: These analyze text data using machine learning methods in order to extract some sort of predictive insight. For example, a topic modeler would be a type of machine learning analysis engine.
4. Visual Analysis Engines: These analyze text data by visualizing it in some way, typically using some sort of graph or map. For example, a word cloud tool would be a type of visual analysis engine.
While the term “analysis engine” is used quite differently within different industries, the general idea is always the same: to extract meaning from text data in order to generate insights that can be used to improve decision making.