Underneath 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 ordered by decreasing reading frequency, i.e. most popular at spot 1.
- MapReduce-Based Pattern Finding Algorithm Applied in Motif Detection for Prescription Compatibility Network
 authors: Yang Liu, Xiaohong Jiang, Huajun Chen , Jun Ma and Xiangyu Zhang – Zhejiang University
- Data-intensive text processing with Mapreduce
 authors: Jimmy Lin and Chris Dyer – University of Maryland
- Large-Scale Behavioral Targeting
 authors: Ye Chen (eBay), Dmitry Pavlov (Yandex Labs) and John F. Canny (University of California, Berkeley)
- Improving Ad Relevance in Sponsored Search
 authors: Dustin Hillard, Stefan Schroedl, Eren Manavoglu, Hema Raghavan and Chris Leggetter (Yahoo Labs)
- Experiences on Processing Spatial Data with MapReduce
 authors: Ariel Cary, Zhengguo Sun, Vagelis Hristidis and Naphtali Rishe – Florida International University
- Extracting user profiles from large scale data
 authors: Michal Shmueli-Scheuer, Haggai Roitman, David Carmel, Yosi Mass and David Konopnicki – IBM Research, Haifa
- Predicting the Click-Through Rate for Rare/New Ads
 authors: Kushal Dave and Vasudeva Varma – IIIT Hyderabad
- Parallel K-Means Clustering Based on MapReduce
 authors: Weizhong Zhao, Huifang Ma and Qing He – Chinese Academy of Sciences
- Storage and Retrieval of Large RDF Graph Using Hadoop and MapReduce
 authors: Mohammad Farhan Husain, Pankil Doshi, Latifur Khan and Bhavani Thuraisingham – University of Texas at Dallas
- Map-Reduce Meets Wider Varieties of Applications
 authors: Shimin Chen and Steven W. Schlosser – Intel Research
- LogMaster: Mining Event Correlations in Logs of Large-scale Cluster Systems
 authors: Wei Zhou, Jianfeng Zhan, Dan Meng (Chinese Academy of Sciences), Dongyan Xu (Purdue University) and Zhihong Zhang (China Mobile Research)
- Efficient Clustering of Web-Derived Data Sets
 authors: Luıs Sarmento, Eugenio Oliveira (University of Porto), Alexander P. Kehlenbeck (Google), Lyle Ungar (University of Pennsylvania)
- A novel approach to multiple sequence alignment using hadoop data grids
 authors: G. Sudha Sadasivam and G. Baktavatchalam – PSG College of Technology
- Web-Scale Distributional Similarity and Entity Set Expansion
 authors: Patrick Pantel, Eric Crestan, Ana-Maria Popescu, Vishnu Vyas (Yahoo Labs) and Arkady Borkovsky (Yandex Labs)
- Grammar based statistical MT on Hadoop
 authors: Ashish Venugopal and Andreas Zollmann (Carnegie Mellon University)
- Distributed Algorithms for Topic Models
 authors: David Newman, Arthur Asuncion, Padhraic Smyth and Max Welling – University of California, Irvine
- Parallel algorithms for mining large-scale rich-media data
 authors: Edward Y. Chang, Hongjie Bai and Kaihua Zhu – Google Research
- Learning Influence Probabilities In Social Networks
 authors: Amit Goyal, Laks V. S. Lakshmanan (University of British Columbia) and Francesco Bonchi (Yahoo! Research)
- MrsRF: an efficient MapReduce algorithm for analyzing large collections of evolutionary trees
 authors: Suzanne J Matthews and Tiffani L Williams – Texas A&M University
- User-Based Collaborative-Filtering Recommendation Algorithms on Hadoop
 authors: Zhi-Dan Zhao and Ming-sheng ShangBest regards, Amund Tveit (Atbrox co-founder) 
 
								
2 Responses to Statistics about Hadoop and Mapreduce Algorithm Papers