Search Results for "learning language"

Part-of-speech tagging is the task of assigning symbols from a particular set to words in a natural language text. ACOPOST implements and extends well-known machine learning techniques and provides a uniform environment for testing.

CRFSharp(aka CRF#) is a .NET(C#) implementation of Conditional Random Fields, an machine learning algorithm for learning from labeled sequences of examples. It is widely used in Natural Language Process (NLP) tasks, for example: word breaker, postagging, named entity recognized, query chunking and so on. CRF#'s mainly algorithm is the same as CRF++ written by Taku Kudo. It encodes model parameters by L-BFGS. Moreover, it has many significant improvement than CRF++, such as totally parallel encoding, optimizing memory usage and so on. ...

TextMarker is now developed and hosted at Apache UIMA (http://uima.apache.org/textmarker.html). TextMarker is a UIMA-based tool for information extraction and more. The full featured editor of the rule language and the build process of UIMA descriptors are complemented with components for visualization, explanation, testing and rule learning.

TBLTools is a set of GATE processing resources that implements the Fast Transformation Based Learning Algorithm. You can train it to learn rules for NLP tasks such as Named Entity Recognition and Shallow parsing.

LT4eL (Language Technology for e-Learning) develops a framework of multilingual language technology tools and semantic web techniques for improving the retrieval and the metadata annotation of learning material.

The TreeQ package is a set of C-language applications that implement a automatic machine learning algorithm based on a tree-structured classifier. This approach is particularly effective for high-dimensional continuous data such as audio and video.