beyond_vector_search

超越矢量搜索
用于增强数据检索的混合矢量/知识图查询引擎

安装

我们使用Python == 3.9.18，建议使用虚拟环境安装所需的软件包。

 pip install -r requirements.txt

创建过滤数据

• notebooks/parsing_json.ipynb的过滤数据
• notebooks/parsing_cnn_news.ipynb新闻的过滤数据
• notebooks/parsing_wiki_movies.ipynb电影的过滤数据

数据集

我们从Kaggle使用了ARXIV数据集的一个子集，其中包含12,926个样本，并且腌制文件提供在“ hewer_vector_search/data/fielded_data.pickle”上。

源代码

 make_vectordb.py: a script to build a vector database from a "data/filtered_data.pickle"

utils/
    - build_graph.py: a script containing helper functions for building the knowledge graph
    - parse_arxiv.py: a script containing helper functions for parsing the arxiv dataset
vector_graph/
    - bipartite_graph_dict.py: A custom implementation of the bipartite graph
    - bipartite_graph_networkx.py: An experimental implementation of the bipartite graph using networkx
    - embedding_models.py: A custom implementation of the embedding models for generating the text embeddings
workloads
    - keyword_extractor.py
    - query_gen.py: A script for generating the text queries given paper data points
    - workload_gen.sh: This is the script for generating the workloads we described in the report
testing
    - inference.py: A script for executing our various search query engines on the generated workloads
zy_testing
    - compute_metrics_cos.py: A script for computing the accuracy of our results utilizing various performance compute_metrics_cos