# yanyiwu/simhash

中文文档simhash值计算

Repository: https://github.com/yanyiwu/simhash
Canonical: https://ross.abutalabs.com/products/simhash
Language: C++
License Family: other
Last push: 2026-07-20T07:02:25+00:00

## Health v2 (maintenance only)
Score: 65/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 93, release rhythm 8, longevity 100
- inputs: {"age_days": 4643, "days_push": 44, "days_rel": 453, "gap_med": null, "n_releases_24m": 1}
- flags: no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1170, forks 263 (observed 2026-08-28T04:03:51.265990+00:00)

## What it is
A C++ header-only library that computes Simhash fingerprints for Chinese documents, using CppJieba for tokenization and keyword extraction. It supports Hamming-distance-based similarity comparison and includes an optional HTTP server for serving Simhash values.

## Use cases
- compute simhash fingerprints for Chinese documents
- detect near-duplicate Chinese web pages or articles
- compare text similarity via Hamming distance
- deduplicate large corpora of Chinese text
- serve simhash calculations over HTTP

## When to choose
- you need fast, near-duplicate detection specifically for Chinese text
- you want a lightweight header-only C++ library with no linking overhead
- you need an embeddable fingerprinting algorithm with tunable keyword counts

## When to avoid
- you need Simhash for non-Chinese languages without adapting the tokenizer
- you need a managed-language (Python/Java) library rather than C++
- you require semantic similarity rather than lexical near-duplicate detection

## Facets
- artifact type: library
- maturity: stable
- function: nlp, search-engine, developer-tools
- domain: developer-tools
- platform: cpp
- tags: simhash, chinese-text, text-deduplication, fingerprinting, hamming-distance, header-only, cppjieba, natural-language-processing, search, linux, macos

## Member repositories
- yanyiwu/simhash (main) score 65

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:03:51.265990+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T06:28:39.377037+00:00, confidence not recorded.
  - readme: https://github.com/yanyiwu/simhash (fetched 2026-08-28T04:03:51.265990+00:00, sha 1e6fc5940830)
- Data as of 2026-08-30T08:39:29.467469+00:00.