# ysc/QuestionAnsweringSystem

QuestionAnsweringSystem是一个Java实现的人机问答系统，能够自动分析问题并给出候选答案。

Repository: https://github.com/ysc/QuestionAnsweringSystem
Canonical: https://ross.abutalabs.com/products/questionansweringsystem
Language: Java
License: Apache-2.0
License Family: permissive
Last push: 2018-08-21T12:59:28+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 4419, "days_push": 2934, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1946, forks 1279 (observed 2026-08-28T04:05:57.757796+00:00)

## What it is
A Java implementation of an open-domain question answering system inspired by IBM Watson, which analyzes questions and returns ranked candidate answers. It supports person, location, organization, number, and time question types, searching multiple data sources and scoring candidates via a web interface and REST API.

## Use cases
- build a question answering system in Java
- automatically answer questions from search results
- implement a Watson-like QA system
- classify question types like person, place, or time
- integrate a QA API into an application

## When to choose
- you need a self-hosted Java QA system with Chinese language support
- you want a reference implementation of the Watson QA pipeline
- you need a REST API that returns ranked candidate answers

## When to avoid
- you need modern LLM-based question answering
- you require active maintenance or recent updates
- you need multilingual support beyond Chinese

## Facets
- artifact type: application
- maturity: maintenance
- function: nlp, search-engine, rag, chatbot
- domain: artificial-intelligence
- platform: jvm, self-hosted
- tags: question-answering, ibm-watson, chinese-nlp, deep-qa, natural-language-processing, search, web-server

## Member repositories
- ysc/QuestionAnsweringSystem (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:05:57.757796+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 2026-08-30T03:07:21.597125+00:00, confidence not recorded.
  - readme: https://github.com/ysc/QuestionAnsweringSystem (fetched 2026-08-28T04:05:57.757796+00:00, sha 3e50451e6987)
- Data as of 2026-08-30T08:39:29.467469+00:00.