本文介绍了ASP.NET Web API的主要特点及使用方法。在此基础上提出了自承载、跨域资源共享、Swagger文档管理、缓存、限流等增强和改进技术。接下来,又提出了针对大量API的接口管理需求及其技术实现方案。进一步地,提出这些技术的集成方...本文介绍了ASP.NET Web API的主要特点及使用方法。在此基础上提出了自承载、跨域资源共享、Swagger文档管理、缓存、限流等增强和改进技术。接下来,又提出了针对大量API的接口管理需求及其技术实现方案。进一步地,提出这些技术的集成方案,并应用于真实工业环境中,现场运行稳定,接口查看和调用方便,为业主创造了巨大经济效益。展开更多
With the ever-increasing popularity of Internet of Things(IoT),massive enterprises are attempting to encapsulate their developed outcomes into various lightweight Web Application Programming Interfaces(APIs)that can b...With the ever-increasing popularity of Internet of Things(IoT),massive enterprises are attempting to encapsulate their developed outcomes into various lightweight Web Application Programming Interfaces(APIs)that can be accessible remotely.In this context,finding and writing a list of existing Web APIs that can collectively meet the functional needs of software developers has become a promising approach to economically and easily develop successful mobile applications.However,the number and diversity of candidate IoT Web APIs places an additional burden on application developers’Web API selection decisions,as it is often a challenging task to simultaneously ensure the diversity and compatibility of the final set of Web APIs selected.Considering this challenge and latest successful applications of game theory in IoT,a Diversified and Compatible Web APIs Recommendation approach,namely DivCAR,is put forward in this paper.First of all,to achieve API diversity,DivCAR employs random walk sampling technique on a pre-built“API-API”correlation graph to generate diverse“API-API”correlation subgraphs.Afterwards,with the diverse“API-API”correlation subgraphs,the compatible Web APIs recommendation problem is modeled as a minimum group Steiner tree search problem.A sorted set of multiple compatible and diverse Web APIs are returned to the application developer by solving the minimum group Steiner tree search problem.At last,a set of experiments are designed and implemented on a real dataset crawled from www.programmableweb.com.Experimental results validate the effectiveness and efficiency of our proposed DivCAR approach in balancing the Web APIs recommendation diversity and compatibility.展开更多
This paper presents a reference methodology for process orchestration that accelerates the development of Large Language Model (LLM) applications by integrating knowledge bases, API access, and deep web retrieval. By ...This paper presents a reference methodology for process orchestration that accelerates the development of Large Language Model (LLM) applications by integrating knowledge bases, API access, and deep web retrieval. By incorporating structured knowledge, the methodology enhances LLMs’ reasoning abilities, enabling more accurate and efficient handling of complex tasks. Integration with open APIs allows LLMs to access external services and real-time data, expanding their functionality and application range. Through real-world case studies, we demonstrate that this approach significantly improves the efficiency and adaptability of LLM-based applications, especially for time-sensitive tasks. Our methodology provides practical guidelines for developers to rapidly create robust and adaptable LLM applications capable of navigating dynamic information environments and performing effectively across diverse tasks.展开更多
详细介绍基于ASP.NET Web API框架设计的校园一卡通手机客户端的实现。通过引用一卡通相关的Web Service,再封装Web API接口供手机端以HTTP方式调用。校园一卡通手机客户端使用户可以利用碎片化时间,随时随地处理校园卡有关业务,突破了...详细介绍基于ASP.NET Web API框架设计的校园一卡通手机客户端的实现。通过引用一卡通相关的Web Service,再封装Web API接口供手机端以HTTP方式调用。校园一卡通手机客户端使用户可以利用碎片化时间,随时随地处理校园卡有关业务,突破了传统校园卡应用的时空局限,开创了新局面。展开更多
文摘本文介绍了ASP.NET Web API的主要特点及使用方法。在此基础上提出了自承载、跨域资源共享、Swagger文档管理、缓存、限流等增强和改进技术。接下来,又提出了针对大量API的接口管理需求及其技术实现方案。进一步地,提出这些技术的集成方案,并应用于真实工业环境中,现场运行稳定,接口查看和调用方便,为业主创造了巨大经济效益。
文摘With the ever-increasing popularity of Internet of Things(IoT),massive enterprises are attempting to encapsulate their developed outcomes into various lightweight Web Application Programming Interfaces(APIs)that can be accessible remotely.In this context,finding and writing a list of existing Web APIs that can collectively meet the functional needs of software developers has become a promising approach to economically and easily develop successful mobile applications.However,the number and diversity of candidate IoT Web APIs places an additional burden on application developers’Web API selection decisions,as it is often a challenging task to simultaneously ensure the diversity and compatibility of the final set of Web APIs selected.Considering this challenge and latest successful applications of game theory in IoT,a Diversified and Compatible Web APIs Recommendation approach,namely DivCAR,is put forward in this paper.First of all,to achieve API diversity,DivCAR employs random walk sampling technique on a pre-built“API-API”correlation graph to generate diverse“API-API”correlation subgraphs.Afterwards,with the diverse“API-API”correlation subgraphs,the compatible Web APIs recommendation problem is modeled as a minimum group Steiner tree search problem.A sorted set of multiple compatible and diverse Web APIs are returned to the application developer by solving the minimum group Steiner tree search problem.At last,a set of experiments are designed and implemented on a real dataset crawled from www.programmableweb.com.Experimental results validate the effectiveness and efficiency of our proposed DivCAR approach in balancing the Web APIs recommendation diversity and compatibility.
文摘This paper presents a reference methodology for process orchestration that accelerates the development of Large Language Model (LLM) applications by integrating knowledge bases, API access, and deep web retrieval. By incorporating structured knowledge, the methodology enhances LLMs’ reasoning abilities, enabling more accurate and efficient handling of complex tasks. Integration with open APIs allows LLMs to access external services and real-time data, expanding their functionality and application range. Through real-world case studies, we demonstrate that this approach significantly improves the efficiency and adaptability of LLM-based applications, especially for time-sensitive tasks. Our methodology provides practical guidelines for developers to rapidly create robust and adaptable LLM applications capable of navigating dynamic information environments and performing effectively across diverse tasks.
