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README
Apache-2.0

AnyQ

AnyQ(ANswer Your Questions) 开源项目主要包含面向FAQ集合的问答系统框架、文本语义匹配工具SimNet。
问答系统框架采用了配置化、插件化的设计,各功能均通过插件形式加入,当前共开放了20+种插件。开发者可以使用AnyQ系统快速构建和定制适用于特定业务场景的FAQ问答系统,并加速迭代和升级。
SimNet是百度自然语言处理部于2013年自主研发的语义匹配框架,该框架在百度各产品上广泛应用,主要包括BOW、CNN、RNN、MM-DNN等核心网络结构形式,同时基于该框架也集成了学术界主流的语义匹配模型,如MatchPyramid、MV-LSTM、K-NRM等模型。SimNet使用PaddleFluid和Tensorflow实现,可方便实现模型扩展。使用SimNet构建出的模型可以便捷的加入AnyQ系统中,增强AnyQ系统的语义匹配能力 (English)

详细介绍

FAQ问答系统框架

AnyQ系统框架主要由Question Analysis、Retrieval、Matching、Re-Rank等部分组成,框架中包含的功能均通过插件形式加入,如Analysis中的中文切词,Retrieval中的倒排索引、语义索引,Matching中的Jaccard特征、SimNet语义匹配特征,当前共开放了20+种插件。AnyQ系统的配置化、插件化设计有助于开发者快速构建、快速定制适用于特定业务场景的FAQ问答系统,加速迭代和升级。 AnyQ的框架结构如下图:

配置化

AnyQ系统集成了检索和匹配的众多插件,通过配置的方式生效;以检索方式和文本匹配相似度计算中的插件为例:

  • 检索方式(Retrieval)
    • 倒排索引:基于开源倒排索引Solr,加入百度开源分词
    • 语义检索:基于SimNet语义表示,使用ANNOY进行ANN检索
    • 人工干预:通过提供精准答案,控制输出
  • 匹配计算(Matching)
    • 字面匹配相似度:在对中文问题进行切词等处理之后,计算字面匹配特征
      • Cosine相似度
      • Jaccard相似度
      • BM25
    • 语义匹配相似度
      • SimNet语义匹配:使用语义匹配SimNet架构训练的模型,构建问题在语义层面的相似度

插件化

除框架外,AnyQ的所有功能都是通过插件形式加入,用户自定义的插件很容易加到AnyQ系统中,只需实现对应的接口即可,如自定义词典加载、Question分析方法、检索方式、匹配相似度、排序方式等,真正实现可定制和插件化。

文本语义匹配框架SimNet

SimNet是百度自然语言处理部于2013年自主研发的语义匹配框架,该框架在百度各产品上广泛应用,主要包括BOW、CNN、RNN、MM-DNN等核心网络结构形式,同时基于该框架也集成了学术界主流的语义匹配模型,如MatchPyramid、MV-LSTM、K-NRM等模型。SimNet使用PaddleFluid和Tensorflow实现,可方便实现模型扩展。使用SimNet构建出的模型可以便捷的加入AnyQ系统中,增强AnyQ系统的语义匹配能力。

按照文本语义匹配网络结构, 可将SimNet中实现的网络模型主要分为如下两类:

  • Representation-based Models 如:BOW, CNN, RNN(LSTM, GRNN) 特点:文本匹配任务的两端输入,分别进行表示,之后将表示进行融合计算相似度;

  • Interaction-based Models 如:MatchPyramid, MV-LSTM, K-NRM, MM-DNN 特点:在得到文本word级别的序列表示之后,根据两个序列表示计算相似度匹配矩阵,融合每个位置上的匹配信息给出最终相似度打分;

SimNet使用PaddleFluid和Tensorflow实现,更多文档请参考:

基于海量搜索数据的语义模型

基于百度海量搜索数据,我们训练了一个SimNet-BOW语义匹配模型,在一些真实的FAQ问答场景中,该模型效果比基于字面的相似度方法AUC提升5%以上,模型使用和获取方法参考Demo

代码编译

Linux

cmake 3.0以上(推荐3.2.2版本),g++ >=4.8.2,bison >=3.0

mkdir build && cd build && cmake .. && make

Others

针对MacOS、Windows等环境,推荐使用docker方式

# paddle官方镜像
docker pull paddlepaddle/paddle:latest-dev
# paddle国内镜像
docker pull hub.baidubce.com/paddlepaddle/paddle:latest-dev

Demo

构建索引、配置

# 获取anyq定制solr,anyq示例配置
cp ../tools/anyq_deps.sh .
sh anyq_deps.sh

# 启动solr, 依赖python-json, jdk>=1.8
cp ../tools/solr -rp solr_script
sh solr_script/anyq_solr.sh solr_script/sample_docs
  • HTTP-Server
./run_server

# 请求示例:
http:${host}:${port}/anyq?question=XXX
  • lib
./demo_anyq sample_input_json

更多文档

如何贡献

  • 可以在AnyQ框架下定制特定功能的插件,教程参考AnyQ如何添加插件
  • 如果觉得自己定制的插件功能足够通用&漂亮,欢迎给我们提交PR

Copyright and License

AnyQ is provided under the Apache-2.0 license.

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简介

AnyQ(ANswer Your Questions) AnyQ(ANswer Your Questions) 开源项目主要包含面向FAQ集合的问答系统框架、文本语义匹配工具Sim 展开 收起
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