Mendeley: Recommendations for Researchers

S. Vargas, Maya Hristakeva, Kris Jack
{"title":"Mendeley: Recommendations for Researchers","authors":"S. Vargas, Maya Hristakeva, Kris Jack","doi":"10.1145/2959100.2959116","DOIUrl":null,"url":null,"abstract":"For a researcher, keeping up with what is going on in their research field can be a difficult and time-consuming task. For example, a fresh PhD student may want to know what are the relevant papers matching their research interests. An assistant professor may like to be up-to-date with what their colleagues are publishing. A professor might want to be notified about funding opportunities relevant to the work done in their research group. Since the volume of published research and research activity is constantly growing, it is becoming increasingly more difficult for researchers to be able to manage and filter through the research information flow. In this challenging context, Mendeley's mission is to become the world's \"research operating system\". We do this not only by providing our well-know reference management system, but also by providing discovery capabilities for researchers on different kinds of entities, such as articles and profiles. In our talk, we will share Mendeley's experiences with building our article and profile recommendation systems, the challenges that we have faced and the solutions that we have put in place. We will discuss how we address different users' needs with our data and algorithm infrastructure to achieve good user experience.","PeriodicalId":315651,"journal":{"name":"Proceedings of the 10th ACM Conference on Recommender Systems","volume":"29 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"11","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 10th ACM Conference on Recommender Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2959100.2959116","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 11

Abstract

For a researcher, keeping up with what is going on in their research field can be a difficult and time-consuming task. For example, a fresh PhD student may want to know what are the relevant papers matching their research interests. An assistant professor may like to be up-to-date with what their colleagues are publishing. A professor might want to be notified about funding opportunities relevant to the work done in their research group. Since the volume of published research and research activity is constantly growing, it is becoming increasingly more difficult for researchers to be able to manage and filter through the research information flow. In this challenging context, Mendeley's mission is to become the world's "research operating system". We do this not only by providing our well-know reference management system, but also by providing discovery capabilities for researchers on different kinds of entities, such as articles and profiles. In our talk, we will share Mendeley's experiences with building our article and profile recommendation systems, the challenges that we have faced and the solutions that we have put in place. We will discuss how we address different users' needs with our data and algorithm infrastructure to achieve good user experience.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
门德利:给研究人员的建议
对于研究人员来说,跟上他们研究领域的进展是一项困难而耗时的任务。例如,一个刚毕业的博士生可能想知道哪些相关论文符合他们的研究兴趣。助理教授可能希望了解同事发表的最新内容。教授可能希望收到与其研究小组所做工作相关的资助机会的通知。由于发表的研究和研究活动的数量不断增长,研究人员越来越难以管理和过滤研究信息流。在这种充满挑战的背景下,门德利的使命是成为世界的“研究操作系统”。我们不仅通过提供众所周知的参考文献管理系统来实现这一目标,而且还为研究人员提供了对不同类型实体(如文章和简介)的发现功能。在我们的演讲中,我们将分享Mendeley在建立我们的文章和简介推荐系统方面的经验,我们面临的挑战以及我们已经实施的解决方案。我们将讨论如何通过我们的数据和算法基础设施来满足不同用户的需求,以实现良好的用户体验。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Opening Remarks Mining Information for the Cold-Item Problem Are You Influenced by Others When Rating?: Improve Rating Prediction by Conformity Modeling Contrasting Offline and Online Results when Evaluating Recommendation Algorithms Intent-Aware Diversification Using a Constrained PLSA
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1