Statistics about Hadoop and Mapreduce Algorithm Papers

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 Shang