首页|基于BiLSTM-CRF模型的房屋出租App系统的设计与实现

基于BiLSTM-CRF模型的房屋出租App系统的设计与实现

扫码查看
针对文本实体信息抽取优化问题,本文以租赁行业为研究对象,首先,使用爬虫技术对客户发布的信息进行爬取,采用BiLSTM-CRF算法对信息进行实体提取和处理,将处理后的信息存储在数据库中,构建App数据来源的数据层,再基于数据层的数据开发App应用层.开发的App应用层模块包括用户认证模块和主页模块.BiLSTM-CRF模型比LSTM和BiLSTM在实体边界的识别率更高,模型准确率、召回率和F1值分别可以达到96.58%,88.94%,92.60%.
Design and Implementation of a Housing Rental App System Based on BiLSTM-CRF Model
In response to the optimization problem of text entity information extraction,this article takes the leasing industry as the research object.Firstly,crawler technology is used to crawl the information published by customers,and the BiLSTM-CRF algorithm is used to extract and process the entity information.The processed information is stored in a database,and a data layer for the App's data source is constructed.Then,an App application layer is developed based on the data from the data layer.The developed App application layer module includes a user authentication module and a homepage module.The BiLSTM-CRF model outperforms LSTM and BiLSTM in entity boundary recognition,with model accuracy,recall,and F1 values reaching 96.58%,88.94%,and 92.60%,respectively.

BiLSTM-CRFdata crawlerApp systementity extraction

罗佳、李萌

展开 >

贵阳人文科技学院,贵州贵阳 550025

贵州慧科未来科技有限公司,贵州贵安 550026

BiLSTM-CRF 数据爬虫 App系统 实体提取

&&

黔教合KY字[2021]116

2024

软件
中国电子学会 天津电子学会

软件

影响因子:1.51
ISSN:1003-6970
年,卷(期):2024.45(1)
  • 5