Prospects of Open Source Software for Maximizing the User Expectations in Heterogeneous Network

Q4 Computer Science

International Journal of Open Source Software and Processes Pub Date : 2018-07-01 DOI:10.4018/IJOSSP.2018070101

Pushpa Singh, R. Agrawal

引用次数: 6

Abstract

This article focuses on the prospects of open source software and tools for maximizing the user expectations in heterogeneous networks. The open source software Python is used as a software tool in this research work for implementing machine learning technique for the categorization of the types of user in a heterogeneous network (HN). The KNN classifier available in Python defines the type of user category in real time to predict the available users in a particular category for maximizing profit for a business organization.

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开源软件在异构网络中最大化用户期望的前景

本文重点讨论在异构网络中最大化用户期望的开源软件和工具的前景。本研究使用开源软件Python作为软件工具，实现异构网络(HN)中用户类型分类的机器学习技术。Python中可用的KNN分类器实时定义用户类别的类型，以预测特定类别中的可用用户，从而使业务组织的利润最大化。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

International Journal of Open Source Software and Processes Computer Science-Software

CiteScore

1.90

自引率

0.00%

发文量

期刊介绍： The International Journal of Open Source Software and Processes (IJOSSP) publishes high-quality peer-reviewed and original research articles on the large field of open source software and processes. This wide area entails many intriguing question and facets, including the special development process performed by a large number of geographically dispersed programmers, community issues like coordination and communication, motivations of the participants, and also economic and legal issues. Beyond this topic, open source software is an example of a highly distributed innovation process led by the users. Therefore, many aspects have relevance beyond the realm of software and its development. In this tradition, IJOSSP also publishes papers on these topics. IJOSSP is a multi-disciplinary outlet, and welcomes submissions from all relevant fields of research and applying a multitude of research approaches.