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University of Waterloo: Logistic Regression and Reciprocal Rank Fusion at the Microblog Track.

机译：滑铁卢大学：微博轨道上的Logistic回归和倒数等级融合。

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摘要

For the second iteration of the Microblog Track, two tasks were given to participants to complete. The first was to perform the same ad hoc search task as the 2011 iteration. The goal of the task was to expand on last year's methods with 60 new topics and

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作者
Roegiest, A.; Cormack, G. V.;
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年度 2012
页码 1-7
总页数 7
原文格式 PDF
正文语种 eng
中图分类工业技术;
关键词
Information retrieval; Canada; Feedback; User needs; Foreign reports; Filtering; Tweets;

机译：信息检索;加拿大;反馈;用户需求;外国报告;过滤;推文;
入库时间 2022-08-29 10:51:38

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1. Rank-Optimized Logistic Matrix Regression toward ImprovedMatrix Data Classification [J] . Jianguang Zhang, Jianmin Jiang Neural computation . 2018,第2期

机译：向改进的矩阵数据分类的秩优化逻辑矩阵回归
2. RANKED TAG RECOMMENDATION SYSTEMS BASED ON LOGISTIC REGRESSION [J] . J. R. Quevedo, E. Montanes, J. Ranilla, Neural Network World . 2010,第7期

机译：基于逻辑回归的排行标签推荐系统
3. Editorial advisory board Professor James H. Bookbinder University of Waterloo, Canada Professor Craig Carter Arizona State University, USA Professor Joseph L. Cavinato Thunderbird School of Global Management, USA Professor Martin Christopher Cranfield School of Management, UK Professor David J. Closs Michigan State University, USA Professor Martha C. Cooper Ohio State University, Fisher College of Business, USA. [J] . International Journal of Physical Distribution & Logistics Management . 2011,第4期

机译：编辑顾问委员会James H. Bookbinder教授，加拿大滑铁卢大学，美国Craig Carter教授，美国亚利桑那州立大学教授Joseph L. Cavinato美国雷鸟全球管理学院教授，Martin Christopher Cranfield管理学院教授，David J. Closs密歇根州立大学教授美国，美国俄亥俄州立大学玛莎·库珀教授，美国费舍尔商学院。
4. Reciprocal rank fusion outperforms condorcet and individual rank learning methods [C] . Gordon V. Cormack, Charles L A Clarke, Stefan Buettcher Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval . 2009

机译：互惠等级融合优于伙伴和个人等级学习方法
5. Preference Probability Based on Ranks - A New Approach Using Logistic Regression with Zero Intercept [D] . Oluwagbenga, Agboola David. 2018

机译：基于秩的偏好概率 - 一种使用零拦截逻辑回归的新方法
6. Your Relevance Feedback Is Essential: Enhancing the Learning to Rank Using the Virtual Feature Based Logistic Regression [O] . Fei Cai, Deke Guo, Honghui Chen, 2009

机译：您的相关反馈至关重要：使用基于虚拟特征的Logistic回归来提高学习排名
7. Reciprocal Rank Fusion outperforms Condorcet and individual Rank Learning Methods [O] . G. V. Cormack, C. L. A. Clarke, Stefan Büttcher 2009

机译：互惠排名融合优于Condorcet和个人排名学习方法

University of Waterloo: Logistic Regression and Reciprocal Rank Fusion at the Microblog Track.

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