论文标题
具有个性特征的社会意识会议参与者建议
Socially-Aware Conference Participant Recommendation with Personality Traits
论文作者
论文摘要
由于在智能会议上进行学术合作的重要性，许多研究人员利用推荐系统为参与者提出有效的建议。最近的研究表明，用户的个性特征可以用作有效建议的创新实体。然而，涉及智能会议参与者个性的主观看法很少见，并且没有得到太多关注。受用户的个性和社会特征的启发，我们提出了一种名为“社会和个性意识到参与者的建议”的算法（SPARP）。我们的建议方法杂交了参与者之间类似的人际关系和人格特质的计算。 Sparp在智能会议上对参与者的个性和社会特征概况进行了建模。通过结合上述建议实体，SPARP随后将参与者互相推荐以进行有效的合作。我们使用相关数据集评估SPARP。实验结果证实了SPARP是可靠的，并且表现优于其他最先进的方法。
As a result of the importance of academic collaboration at smart conferences, various researchers have utilized recommender systems to generate effective recommendations for participants. Recent research has shown that the personality traits of users can be used as innovative entities for effective recommendations. Nevertheless, subjective perceptions involving the personality of participants at smart conferences are quite rare and haven't gained much attention. Inspired by the personality and social characteristics of users, we present an algorithm called Socially and Personality Aware Recommendation of Participants (SPARP). Our recommendation methodology hybridizes the computations of similar interpersonal relationships and personality traits among participants. SPARP models the personality and social characteristic profiles of participants at a smart conference. By combining the above recommendation entities, SPARP then recommends participants to each other for effective collaborations. We evaluate SPARP using a relevant dataset. Experimental results confirm that SPARP is reliable and outperforms other state-of-the-art methods.
