Recommendation of microblog users based on hierarchical interest profiles

Author:

Faralli Stefano,Stilo Giovanni,Velardi PaolaORCID

Publisher

Springer Science and Business Media LLC

Subject

Computer Science Applications,Human-Computer Interaction,Media Technology,Communication,Information Systems

Reference48 articles.

1. Agrawal R, Srikant R (1994) Fast algorithms for mining association rules in large databases. Proceedings of the 20th International Conference on Very Large Data Bases., VLDB ’94Morgan Kaufmann Publishers Inc. San Francisco, pp 487–499

2. Armentano M, Godoy D, Amandi A (2011) A topology-based approach for followees recommendation in twitter. In: 9th Workshop on Intelligent Techniques for Web Personalization and Recommender Systems. Barcelona, Spain

3. Aroyo L, Welty C (2013) Crowd Truth: Harnessing disagreement in crowdsourcing a relation extraction gold standard. In: Proceedings of ACM Web Science. Paris, France

4. Barbieri N, Manco G, Bonchi F (2014) Who to follow and why: Link prediction with explanations. In: Proceedings of The 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD 2014). New York City

5. Burger JD, Henderson J, Kim G, Zarrella G (2011) Discriminating Gender on Twitter. In: Proceedings of the Conference on Empirical Methods in Natural Language Processing. Edinburgh, Scotland, pp 1301–1309

Cited by 14 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. The rise of user profiling in social media: review, challenges and future direction;Social Network Analysis and Mining;2023-10-19

2. Analyzing Features of Passive Twitter’s Users to Estimate Passive Twitter-User’s Interests;IEEE/WIC/ACM International Conference on Web Intelligence;2021-12-14

3. Topic-model based Estimation of Passive Twitter-User's Interests from Followed Users' Tweets;2021 10th International Congress on Advanced Applied Informatics (IIAI-AAI);2021-07

4. WhoSNext: Recommending Twitter Users to Follow Using a Spreading Activation Network Based Approach;2020 International Conference on Data Mining Workshops (ICDMW);2020-11

5. Extracting, Mining and Predicting Users’ Interests from Social Media;Foundations and Trends® in Information Retrieval;2020

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3