go-ego/gse

What it solves

gse is a high-performance, multilingual text segmentation and NLP library for Go. It solves the problem of breaking down continuous text (especially in languages like Chinese and Japanese where words aren't separated by spaces) into meaningful words or tokens for further analysis, search indexing, and natural language processing.

How it works

The library implements a Go version of the jieba algorithm and extends it with additional NLP capabilities. It uses a Double-Array Trie for efficient dictionary lookups and employs several segmentation modes:

• Shortest Path/DAG: Uses word frequency and dynamic programming to find the optimal segmentation.
• HMM (Hidden Markov Model): Uses the Viterbi algorithm to cut text, which is particularly useful for recognizing new words not in the dictionary.

It supports multiple modes including common, search engine, full, and precise modes, and allows for the use of custom user dictionaries and stop-word lists.

Who it’s for

Developers building search engines, text analysis tools, or any Go-based application that requires multilingual text processing, specifically for East Asian languages.

Highlights

• Multilingual Support: Works with English, Chinese (Simplified and Traditional), and Japanese.
• Multiple Segmentation Modes: Offers precise, full, search engine, and HMM-based cutting.
• Integration: Compatible with Elasticsearch, Bleve, and ZincSearch.
• NLP Features: Includes Part-of-Speech (POS) tagging and Named Entity Recognition (in progress).
• High Performance: Optimized for speed, supporting concurrent processing via goroutines.