利用社交媒体的个性特征信息进行音乐推荐

Abhishek Paudel, Brihat Ratna Bajracharya, Miran Ghimire, Nabin Bhattarai, D. S. Baral
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引用次数: 8

摘要

音乐是我们生活中不可或缺的一部分。人们每天都根据自己的口味和心情听音乐。随着数字内容的进步和数量的增加,人们收听不同类型音乐的选择也大大增加。因此,向听众提供最适合的音乐的必要性一直是计算机科学中一个有趣的研究领域。向听众提供最佳音乐的重要标准之一可能是他们的个性特征。为了确定一个人的个性特征,像Facebook这样的社交媒体可以是一个有用的平台,人们可以在这里表达他们对不同问题的看法,分享他们的观点和想法。本文首先描述了使用朴素贝叶斯分类器使用基本的自然语言处理技术,根据一个人在Facebook上的状态更新来确定一个人的标准大五人格特征,然后介绍了使用由此获得的人格特征信息来增强广泛实施的用户对用户协同过滤技术,用于音乐推荐。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Using Personality Traits Information from Social Media for Music Recommendation
Music is an integral part of our life. People listen to music everyday as per their taste and mood. With the advancement and increase in volume of digital content, the choice for people to listen to diverse type of music has also increased significantly. Thus, the necessity of delivering the most suited music to the listeners has been an interesting field of research in computer science. One of the important measures to deliver the best music to listeners could be their personality traits. In order to determine the personality traits of a person, social media like Facebook can be a useful platform where people express their views on different matters, share their opinions and thoughts. This paper first describes the use of Naive Bayes classifier to determine the standard Big Five Personality Traits of a person based on their status updates on Facebook profile using basic natural language processing techniques, and then proceeds to present the use of thus obtained information about personality traits to enhance the widely implemented user-to-user collaborative filtering techniques for music recommendation.
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