Concept Matrix
Wikipedia™ is a fantastic lexical analysis resource.  It will probably be one of the most important elements in bringing up a true artificial intelligence, but first we have to figure out how m
Concept Topics
Other kinds of text mining categorizers take lots of work to set up and/or are inherently brittle.A conservative estimate for a query based categorizer with 100 buckets is probably on the order of 50
Salience Facets: A New Way
Get more out of your text analysis software with Salience Facets from Lexalytics.
Document Collection Processing
Prior to Salience Five, there was only one way to process content throu
Sentiment Extraction: Measuring the Emotional Tone of Text
Sentiment scoring is emotion!  Is the text positive or negative?  Good or bad?  How will you know if you don't look?  How can you look by hand if its millions of comments per hour?
Named Entity and Theme Sentiment Analysis
Except for press releases, it’s rare to find a document that is  homogenously positive or negative.
Named Entity Extraction
Lexalytics' text analysis software supports five different methods for extracting named entities from your text.  Named entities are important in that our soft
Determining Context: Clustering, N-grams, Part-of-Speech-Based Extraction, Themes, and Facets
The “bread and butter” text analytics operations are: “who is being discussed”, “what is the context of the conversation”, and “what is the tone/sentiment of that conversation”. This
Themes: Best of All Worlds
In the opinion mining process, themes are noun phrases with contextual relevance scores.
Summarization is an algorithmic shortening of the input content so as to best represent the whole content in a limited amount of words to enhance the text analysis process.    &nbs
There's a lot of ways of saying the same thing: how do I sort content into different buckets.For example, if I see the following text: I wonder who will win in the California mid-term congression
Multi-Lingual Support
Multi-Lingual support is a subset of our data directory technology, which includes optimizations for sentiment analysis and named entity recognition and extraction to analyze social media, such as Twi
Text Preparation
Yes, it's a relatively boring topic. 


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