# NTMC-Community/MatchZoo

Facilitating the design, comparison and sharing of deep text matching models.

Repository: https://github.com/NTMC-Community/MatchZoo
Canonical: https://ross.abutalabs.com/products/matchzoo
Language: Python
License: Apache-2.0
License Family: permissive
Topics: text, matching, deep-learning, text-matching, neural-network, natural-language-processing
Last push: 2024-08-02T16:23:45+00:00

## Health v2 (maintenance only)
Score: 23/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 0, release rhythm 8, longevity 100
- inputs: {"age_days": 3373, "days_push": 761, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 3849, forks 891 (observed 2026-08-28T04:08:24.228787+00:00)

## What it is
MatchZoo is a Python toolkit for designing, comparing, and sharing deep text matching models. It provides a unified data pipeline, pre-built models, and hyper-parameter tuning for tasks like document retrieval, question answering, and paraphrase identification.

## Use cases
- build deep learning models for text matching
- rank documents for a search query
- identify paraphrase pairs with neural networks
- train a question-answer matching model
- compare different semantic matching architectures
- benchmark conversational response ranking models

## When to choose
- you need a unified framework to experiment with many text matching models
- you want prebuilt implementations of classic matching models like DRMM or Match-LSTM
- you are doing research on semantic matching and need reproducible baselines

## When to avoid
- you need a production-ready serving system rather than a research toolkit
- you prefer PyTorch, in which case MatchZoo-py is the better fit
- you need general-purpose NLP beyond text pair matching

## Facets
- artifact type: library
- maturity: maintenance
- function: machine-learning, nlp, deep-learning
- domain: deep-learning
- platform: python
- tags: text-matching, semantic-matching, information-retrieval, question-answering, paraphrase-identification, ranking, research-toolkit, natural-language-processing, search

## Member repositories
- NTMC-Community/MatchZoo (main) score 23

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:08:24.228787+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 2026-08-29T18:25:58.605587+00:00, confidence not recorded.
  - readme: https://github.com/NTMC-Community/MatchZoo (fetched 2026-08-28T04:08:24.228787+00:00, sha 1c7d42eec8f4)
  - registry_pypi: https://pypi.org/pypi/matchzoo/json (fetched 2026-08-29T09:20:33.767233+00:00, sha 716a63ce85b5)
- Data as of 2026-08-30T08:39:29.467469+00:00.