機(jī)器學(xué)習(xí)Statistics about Hadoop and Mapreduce Algorith

1、Statistics about Hadoop and Mapreduce Algorithm Paperscloud computing Add commentsUnderneath are statistics about which 20 papers (of about 80 papers) were most read in our 3 previous postings about mapreduce and hadoop algorithms (the postings have been read approximately 5000 times). The list is o

2、rdered by decreasing reading frequency, i.e. most popular at spot 1.1. MapReduce-Based Pattern Finding Algorithm Applied in Motif Detection for Prescription Compatibility Networkauthors: Yang Liu, Xiaohong Jiang, Huajun Chen , Jun Ma and Xiangyu Zhang Zhejiang University 2. Data-intensive text proce

3、ssing with Mapreduceauthors: Jimmy Lin and Chris Dyer University of Maryland 3. Large-Scale Behavioral Targetingauthors: Ye Chen (eBay), Dmitry Pavlov (Yandex Labs) and John F. Canny (University of California, Berkeley) 4. Improving Ad Relevance in Sponsored Searchauthors: Dustin Hillard, Stefan Sch

4、roedl, Eren Manavoglu, Hema Raghavan and Chris Leggetter (Yahoo Labs) 5. Experiences on Processing Spatial Data with MapReduceauthors: Ariel Cary, Zhengguo Sun, Vagelis Hristidis and Naphtali Rishe Florida International University 6. Extracting user profiles from large scale dataauthors: Michal Shmu

5、eli-Scheuer, Haggai Roitman, David Carmel, Yosi Mass and David Konopnicki IBM Research, Haifa 7. Predicting the Click-Through Rate for Rare/New Adsauthors: Kushal Dave and Vasudeva Varma IIIT Hyderabad 8. Parallel K-Means Clustering Based on MapReduceauthors: Weizhong Zhao, Huifang Ma and Qing He Ch

6、inese Academy of Sciences 9. Storage and Retrieval of Large RDF Graph Using Hadoop and MapReduceauthors: Mohammad Farhan Husain, Pankil Doshi, Latifur Khan and Bhavani Thuraisingham University of Texas at Dallas 10. Map-Reduce Meets Wider Varieties of Applicationsauthors: Shimin Chen and Steven W. S

7、chlosser Intel Research 11. LogMaster: Mining Event Correlations in Logs of Large-scale Cluster Systemsauthors: Wei Zhou, Jianfeng Zhan, Dan Meng (Chinese Academy of Sciences), Dongyan Xu (Purdue University) and Zhihong Zhang (China Mobile Research) 12. Efficient Clustering of Web-Derived Data Setsa

8、uthors: Lus Sarmento, Eugenio Oliveira (University of Porto), Alexander P. Kehlenbeck (Google), Lyle Ungar (University of Pennsylvania) 13. A novel approach to multiple sequence alignment using hadoop data gridsauthors: G. Sudha Sadasivam and G. Baktavatchalam PSG College of Technology 14. Web-Scale

9、 Distributional Similarity and Entity Set Expansionauthors: Patrick Pantel, Eric Crestan, Ana-Maria Popescu, Vishnu Vyas (Yahoo Labs) and Arkady Borkovsky (Yandex Labs) 15. Grammar based statistical MT on Hadoopauthors: Ashish Venugopal and Andreas Zollmann (Carnegie Mellon University) 16. Distribut

10、ed Algorithms for Topic Modelsauthors: David Newman, Arthur Asuncion, Padhraic Smyth and Max Welling University of California, Irvine 17. Parallel algorithms for mining large-scale rich-media dataauthors: Edward Y. Chang, Hongjie Bai and Kaihua Zhu Google Research 18. Learning Influence Probabilities In Social Networksauthors: Amit Goyal, Laks V. S. Lakshmanan (University of British Columbia) and Francesco Bonchi (Yahoo! Research) 19. MrsRF: an efficient MapReduce algorithm for analyzing large collections of evolutionary treesauthors: Suzanne J Ma