NLPchina/nlp-lang

What it solves

It provides a foundational set of common utilities and components needed for Natural Language Processing (NLP) projects, reducing the need to build basic text processing tools from scratch.

How it works

The project acts as a basic package that encapsulates various NLP tools. It includes algorithms for text segmentation, word normalization, and similarity calculations, as well as data structures like Trie trees and Bloom filters for efficient text handling.

Who it’s for

Developers building NLP applications who need a reliable set of Java-based utility libraries for text cleaning, normalization, and statistical analysis.

Highlights

• Word normalization and text sentence breaking.
• Implementation of the Viterbi algorithm.
• Chinese-specific tools such as Hanzi to Pinyin conversion and Simplified/Traditional Chinese conversion.
• Text similarity and deduplication using SimHash and fingerprinting.
• Statistical tools for word frequency, IDF, and category relevance.