论文标题

通过机器学习技术检测室友兼容性检测

Roommate Compatibility Detection Through Machine Learning Techniques

论文作者

Lamba, Mansha, Goswami, Raunak, Vinay, Lamba, Mohit

论文摘要

我们的目标是开发一个人为智​​能的系统,旨在检查相同或不同性别共享居住区域的室友之间的兼容性。有一些关键因素决定一个人与对方的兼容性。人际行为,情境意识,沟通技巧。在这里,我们试图构建一个系统,该系统不是通过笔纸测试来评估这些关键因素,而是通过一组高度吸引人的问题和答案来评估用户。因此,使用这些分数作为我们机器学习算法的输入,该算法基于以前的趋势,以提出用户与其他用户兼容的百分比概率。随着人口的增长,组织和教育机构始终面临挑战,使学生及其员工的生产力越来越高,在这种情况下,一个人的社交环境就会发挥作用。一个人可能是一个天才,但只要他不能与同龄人合作,就总是有机会提高生产力。人类一直是一个社会动物,这是一个公认的事实,这有助于建立志同道合的人的社区。很多时候,即使有很多人雇用执行特定任务的人,结果可能并不像人们在彼此合作中不兼容的那样预期。最终,这会产生绩效差距,阻碍组织的成功,并在许多情况下损失宝贵的资源。我们的目的是不是从图片中删除不兼容的人,而是要找到其他地方的人的完美兼容匹配,而不仅可以节省资源,还将有效利用资源。通过使用各种机器学习分类技术,我们打算这样做。

Our objective is to develop an artificially intelligent system which aims at checking the compatibility between the roommates of same or different sex sharing a common area of residence. There are a few key factors determining one's compatibility with the other person. Interpersonal behaviour , situational awareness, communication skills. Here we are trying to build a system that evaluates user on these key factors not via pen paper test but through a highly engaging set of questions and answers. Hence using these scores as an input to our machine learning algorithm which is based on previous trends to come up with percentage probability of user being compatible with another user. With the growing population there is always a challenge for organisation and educational institutions to make the students and their employees more and more productive and in such cases a person's social environment comes into play. A person may be a genius but as long as he is not able to work well with his peers there will always be a chance of more productive performance. It is a well-established fact that human are and have always been a social animal and this has helped in creating communities of like-minded people. Many times, even when there are a large no of people employed to do a particular task the result may not be as expected as people may not compatible in working with one another. This at the end creates performance gaps, hinders organisation success and in many cases loss of precious resources. Our intent is not to remove the non-compatible people from the picture but to find out the perfect compatible match for the person elsewhere that will not only save the resources will also enable effective use of resources. Through the use of various machine learning classification techniques, we intent to do this.

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