面向新型农村社区的就业信息管理系统

发布时间：2018-01-05 00:09

本文关键词：面向新型农村社区的就业信息管理系统　出处：《河南农业大学》2015年硕士论文　论文类型：学位论文

【摘要】：本文针对新型农村社区为载体的就业市场,以提高社区就业信息的集成性、信息获取的便捷性和信息服务的准确性为目标,采取以社区做为信息管理服务基本单元,通过信息协同,实现社区间信息共享,设计就业信息管理系统体系结构,并基于个性化技术、信息抓取等技术,建立面向新型农村社区的就业信息管理系统,为社区居民、小微企业和新型农村生产组织提供便捷的就业信息服务,主要内容包括:(1)以新型农村社区为对象,在就业信息服务业务逻辑分析的基础上,采取以行政社区做为信息服务的基本单元,设计两层业务逻辑结构,建立由中心域、社区域组成的两级域网络模型,构建由信息查询、信息发布、信息推送、信息抓取等模块组成的功能模型,依据资源类型和就业信息资源目录模型,设计用户角色模型等,据此形成面向新型农村社区的就业信息管理系统体系结构。(2)设计面向新型农村社区的就业信息资源目录,基于就业信息服务核心信息(如用工信息、实用信息),结合行业分类、职业分类、行政区划、政策分类等,建立就业信息资源目录模型,基于数据流和数据字典,建立就业信息数据关系模型,包括社区、企业、用工、实用和人才等5类信息,进行数据规范性设计。(3)构建基于用户兴趣模型的就业信息个性化服务,采用向量空间模型,对用户兴趣特征与用工信息特征进行表示,通过对用户行为的跟踪记录,建立用户兴趣模型,采用渐进遗忘的方法进行动态更新,最终计算用户兴趣特征向量与用工信息特征向量的相似度,进行推荐。通过个性化就业信息推荐服务实验,查全率达到76.11%,查准率达到85.29%,F-调和均值达到0.8,结果表明,可以为便捷的信息获取提供技术手段,实现就业信息的个性化推送。(4)提出基于自适应阈值的网页正文抽取算法,以基于文本密度的正文抽取做为基础算法,结合大律法,构建基于自适应阈值的网页正文抽取算法。通过对“中华人民共和国人力资源和社会保障部”、“河南省人力资源和社会保障厅”和“新浪网”等网页正文抽取对比实验,正文提取率分别达到90%、92%、64%等,结果表明,可以为定向就业信息采集提供技术支持,实现就业信息的高效获取。本文定位新型农村社区,通过“社区-雇主-用户”模式进行系统应用,可以为农村地区提供专业的、精准的、细分市场的就业信息服务,有利于海量的农村就业信息资源的组织、管理与共享,为广大新农村社区提供高效、优质、规范、透明的就业服务,使不同层次的用户可以便捷的获取就业信息,改善就业信息服务的实际操作性和经济性,提高农村社区居民的就业率和就业信息获取能力,提升就业信息服务的效率和价值。
[Abstract]:This paper aims at improving the integration of community employment information, the convenience of obtaining information and the accuracy of information service for the employment market with new rural communities as the carrier. Take the community as the basic unit of information management service, realize information sharing among communities through information collaboration, design the system structure of employment information management system, and based on personalized technology, information capture and other technologies. The establishment of a new rural community oriented employment information management system for community residents, small and micro enterprises and new rural production organizations to provide convenient employment information services. The main contents include: 1) take the new rural community as the object, on the basis of the business logic analysis of employment information service, take the administrative community as the basic unit of information service, design the two-tier business logic structure. A two-level domain network model consisting of central domain and community domain is established, and a functional model composed of information query, information publishing, information push, information capture and so on is constructed. According to the resource type and employment information resource catalog model, the user role model is designed. According to this, the employment information management system architecture for the new rural community is formed. The employment information resource catalogue for the new rural community is designed, which is based on the core information of employment information service (such as employment information). Practical information, combining industry classification, occupation classification, administrative division, policy classification and so on, establishes the employment information resource catalog model, based on the data flow and data dictionary, establishes the employment information data relation model. Including the community, enterprise, employment, practical and human resources and other five types of information, data normative design. 3) based on user interest model of employment information personalized service, using vector space model. The characteristics of user interest and employment information are represented, and the user interest model is established by tracking the user behavior and updating dynamically with the method of gradual forgetting. Finally, the similarity between the feature vector of user interest and the feature vector of employment information is calculated and recommended. Through the experiment of personalized employment information recommendation service, the recall rate reaches 76.11%. The precision rate of 85.29 F- and the mean value reached 0.8, the results show that it can provide a technical means for convenient information acquisition. To realize the personalized push of employment information, we propose an adaptive threshold based text extraction algorithm, which combines the text extraction based on text density with the Great Law. The text extraction algorithm based on adaptive threshold is constructed through the "Ministry of Human Resources and Social Security of the people's Republic of China". "Henan Human Resources and Social Security Department" and "Sina.com" and other web page text extraction comparative experiment, the text extraction rate reached 90, 922%, the results show. It can provide technical support for the collection of targeted employment information and realize the efficient acquisition of employment information. This paper aims at the new rural community and applies it systematically through the mode of "community-employer-user". Can provide professional, accurate, subdivision of employment information services for rural areas, conducive to massive rural employment information resources organization, management and sharing, for the vast number of new rural communities to provide efficient, high-quality. Standardized, transparent employment services, so that users at different levels can easily obtain employment information, improve the actual operation and economy of employment information services. To improve the employment rate of rural community residents and the ability of obtaining employment information, and to improve the efficiency and value of employment information service.
【学位授予单位】：河南农业大学
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：F249.2;D422.6

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