Search Results for "root"

...The WNLT project delivers four core NLP modules; a) Word Segmentation for separating text into words b) Sentence Boundary Disambiguation for finding sentence boundaries c) Part of Speech Tagger for determining the part of speech of each word d) Morphological Analyser for identifying the root form (lemma) of words. The modules are written in JAVA and ‘wrapped’ for execution under the General Architecture for Text Engineering (GATE) framework. The project also includes CYMRIE an adapted version for Welsh of the GATE - ANNIE Named Entity Recognition (NER) application for a range of entities such as Persons, Organisations, Locations, and date and time expressions. ...

...The WNLT project delivers four core NLP modules; a) Word Segmentation for separating text into words b) Sentence Boundary Disambiguation for finding sentence boundaries c) Part of Speech Tagger for determining the part of speech of each word d) Morphological Analyser for identifying the root form (lemma) of words. The modules are written in JAVA and ‘wrapped’ for execution under the General Architecture for Text Engineering (GATE) framework. The project also includes CYMRIE an adapted version for Welsh of the GATE - ANNIE Named Entity Recognition (NER) application for a range of entities such as Persons, Organisations, Locations, and date and time expressions.

This is a Gujarati stemmer in Java. Stemming is a process in which affixes are removed form the root word (stem). It relates morphological variant words to corresponding common root. For example "પ્રતિઉપયોગી" is word which has stem " ઉપયોગ". Stemmers are language specific tools. The design of a stemming algorithm requires a significant level of linguistic expertise. There has been lot of significant work in the development and evaluation of stemmer for non-Indian languages, but very less or no significant work has been done on Indian front especially for Gujarati language.The code of this stemmer is based on algorithm designed under guidance of Prof. ...

Using Machine Learning, AraRooter finds the three-lettered root of any Arabic lemma with around 84% accuracy.

The Stemmer class transforms a word into its root form. The input word is provided from the add() methods. The stem() method will return the stem as will toString() after stem() has been called). The clear() method will wipe the Stemmer buffer and allow a new word to be input. This version extends Martin Porter's original stemming algorithm by allowing capital letters to exist in words.