Download Seminar Papers from ACM SIGMOD conference 2002 proceeding are:

Winter 2015, 60-539 Seminar Topic List from ACM KDD 2014, ACM SIGMOD 2014
and VLDB 2014 conference proceedings or some earlier articles in the Most cited list.
Please, select your seminar paper (equivalent to a full paper of 8 to 15 pages), obtain it
from the web and make copies available to your seminar grading group (this time
consisting of the entire class). Use the provided information for around 8 people in the
seminar grading group that will be grading your seminar so you can make copies of your
paper for them. There may be only one seminar grading group if not more than 10
students in class. You can select more than one paper to have equivalent of a full paper if
you select papers with fewer pages.
Seminar papers from ACM KDD 2014 (listed in section A) and SIGMOD conference
proceedings 2014 (listed in section B) can be obtained through the university of Windsor
online ACM digital library: go to http://www.uwindsor.ca, click on library, click on Find
Journal Articles and Research Tools, then by subject, Computer Science, click on ACM
digital library, log on with your library card bar code or UWindsor userid and password,
and look for proceedings, then look for ACM KDD or SIGMOD 2014, look for your
seminar paper and print it. Papers from VLDB conference proceedings are listed in
section C and can be downloaded directly through www.google.com or through
http://www.vldb.org/pvldb/vol8.html.
A. Seminar Papers from ACM SIGKDD conference proceedings. Please, provide full
particulars of the paper when picked. To download these papers, go to
www.uwindsor.ca/leddy, click on “Journal Articles & Research Tools” and then
“Computer Science”, go to “ACM digital library” and then Special Interest Groups(SIG),
click on “Archive”. Then, scroll down to SIGKDD (KDD 14) to download the papers.
A1. These papers are from the 10 most downloaded list (not just 2014 proceedings)
1. The WEKA data mining software: an update – 2009, Mark Hall, Eibe Frank,
Geoffrey Holmes, Bernhard Pfahringer, Peter Reutemann, Ian H. Witten, pages 1018
2.
A cost-effective recommender system for taxi drivers – 2014, Meng Qu, Hengshu
Zhu, Junming Liu, Guannan Liu, Hui Xiong, pages 45-54.
3. Maximizing the spread of influence through a social network – 2003, David Kempe,
Jon Kleinberg, Éva Tardos , pp. 137-146
4. The battle for the future of data mining – 2014, Oren Etzioni, pp 1-1
5. Finding high-quality content in social media – 2008, Eugene Agichtein, Carlos
Castillo, Debora Donato, Aristides Gionis, Gilad Mishne, pp 183-194
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6. COM: a generative model for group recommendation – 2014, Quan Yuan, Gao
Cong, Chin-Yew Lin, pp 163-172
7. The YouTube video recommendation system – 2010, James Davidson, Benjamin
Liebald, Junning Liu, Palash Nandy, Taylor Van Vleet, Ullas Gargi, Sujoy Gupta, Yu
He, Mike Lambert, Blake Livingston, Dasarathi Sampath, 293-296
8. Mining big data: current status, and forecast to the future – 2013, Wei Fan, Albert
Bifet, pp 1-5.
9. Prediction of human emergency behavior and their mobility following large-scale
disaster – 2014, Xuan Song, Quanshi Zhang, Yoshihide Sekimoto, Ryosuke
Shibasaki, pp 5-14.
10.
We know what you want to buy: a demographic-based system for product
recommendation on microblogs – 2014, Xin Wayne Zhao, Yanwei Guo, Yulan He,
Han Jiang, Yuexin Wu, Xiaoming Li, pp 1935-1944.
A2. From KDD 14 conference proceedings:
11.
Prediction of human emergency behavior and their mobility following large-scale
disaster, Xuan Song, Quanshi Zhang, Yoshihide Sekimoto, Ryosuke Shibasaki,
Pages: 5-14
12.
Inferring user demographics and social strategies in mobile social networks
Yuxiao Dong, Yang Yang, Jie Tang, Yang Yang, Nitesh V. Chawla, Pages: 15-24
13.
Travel time estimation of a path using sparse trajectories Yilun Wang, Yu Zheng,
Yexiang Xue, Pages: 25-34
14. LUDIA: an aggregate-constrained low-rank reconstruction algorithm to leverage
publicly released health data, Yubin Park, Joydeep Ghosh, Pages: 55-64
15. Scalable noise mining in long-term electrocardiographic time-series to predict death
following heart attacks, Chih-Chun Chia, Zeeshan Syed, Pages: 125-134.
16. Jointly modeling aspects, ratings and sentiments for movie recommendation
(JMARS), Qiming Diao, Minghui Qiu, Chao-Yuan Wu, Alexander J. Smola, Jing Jiang,
Chong Wang, Pages: 193-202
17. Relevant overlapping subspace clusters on categorical data, Xiao He, Jing Feng,
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Bettina Konte, Son T. Mai, Claudia Plant, Pages: 213-222
18. Batch discovery of recurring rare classes toward identifying anomalous samples, Murat
Dundar, Halid Ziya Yerebakan, Bartek Rajwa, Pages: 223-232
19. Representative clustering of uncertain data, Andreas Züfle, Tobias Emrich, Klaus Arthur
Schmid, Nikos Mamoulis, Arthur Zimek, Matthias Renz, Pages: 243-252.
20. Scaling out big data missing value imputations: pythia vs. godzilla, Christos
Anagnostopoulos, Peter Triantafillou, Pages: 651-660
21. Top-k frequent itemsets via differentially private FP-trees, Jaewoo Lee, Christopher W.
Clifton, Pages: 931-940
22. Grouping students in educational settings, Rakesh Agrawal, Behzad Golshan, Evimaria
Terzi, Pages: 1017-1026
23. Methods for ordinal peer grading, Karthik Raman, Thorsten Joachims, Pages: 10371046
24. Mining topics in documents: standing on the shoulders of big data, Zhiyuan Chen, Bing
Liu, Pages: 1116-1125
25. Integrating spreadsheet data via accurate and low-effort extraction, Zhe Chen, Michael
Cafarella, Pages: 1126-1135
26. Activity-edge centric multi-label classification for mining heterogeneous information
networks, Yang Zhou, Ling Liu, Pages: 1276-1285
27. Minimizing seed set selection with probabilistic coverage guarantee in a social
network, Peng Zhang, Wei Chen, Xiaoming Sun, Yajun Wang, Jialin Zhang, Pages:
1306-1315
28. B. Seminar Papers from ACM SIGMOD Conference 2014
Follow the same steps as described for A above and find Sigmod 2014 papers.
29. Lazy evaluation of transactions in database systems, Jose M. Faleiro, Alexander
Thomson, Daniel J. Abadi, Pages: 15-26
30. JECB: a join-extension, code-based approach to OLTP data partitioning, Khai Q.
Tran, Jeffrey F. Naughton, Bruhathi Sundarmurthy, Dimitris Tsirogiannis, Pages: 3950
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31. Influence maximization: near-optimal time complexity meets practical efficiency,
Youze Tang, Xiaokui Xiao, Yanchen Shi, Pages: 75-86
32. Efficient location-aware influence maximization, Guoliang Li, Shuo Chen,
Jianhua Feng, Kian-lee Tan, Wen-syan Li, Pages: 87-98
33.AutoPlait: automatic mining of co-evolving time sequences, Yasuko
Matsubara, Yasushi Sakurai, Christos Faloutsos, Pages: 193-204
34. Resource-oriented approximation for frequent itemset mining from bursty
data streams, Yoshitaka Yamamoto, Koji Iwanuma, Shoshi Fukuda, Pages: 205216
35. Complex event analytics: online aggregation of stream sequence patterns,
Yingmei Qi, Lei Cao, Medhabi Ray, Elke A. Rundensteiner, Pages: 229-240
36. LINVIEW: incremental view maintenance for complex analytical queries,
Milos Nikolic, Mohammed ElSeidy, Christoph Koch, Pages: 253-264
37. Efficient summarization framework for multi-attribute uncertain data,
Jie Xu, Dmitri V. Kalashnikov, Sharad Mehrotra, Pages: 421-432
38.Descriptive and prescriptive data cleaning, Anup Chalamalla, Ihab F.
Ilyas, Mourad Ouzzani, Paolo Papotti, Pages: 445-456
39. Towards dependable data repairing with fixing rules, Jiannan Wang,
Nan Tang, Pages: 457-468
40. A sample-and-clean framework for fast and accurate query
processing on dirty data, Jiannan Wang, Sanjay Krishnan, Michael J.
Franklin, Ken Goldberg, Tim Kraska, Tova Milo, Pages: 469-480
41. Opportunistic physical design for big data analytics, Jeff LeFevre,
Jagan Sankaranarayanan, Hakan Hacigumus, Junichi Tatemura,
Neoklis Polyzotis, Michael J. Carey, Pages: 851-862
C. Seminar Papers from the VLDB (Conference on Very Large Databases)
2014 are:
You may get these papers through searching for VLDB 2012 conference
paper with www.google.com or through
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http://www.informatik.uni-trier.de/~ley/db/journals/pvldb/pvldb4.html.
42. Yifang Sun, Wei Wang, Jianbin Qin, Ying Zhang, Xuemin Lin:
SRS: Solving c-Approximate Nearest Neighbor Queries in High Dimensional Euclidean
Space with a Tiny Index. 1 - 12.
43. Michele Dallachiesa, Themis Palpanas, Ihab F. Ilyas:
Top-k Nearest Neighbor Search In Uncertain Data Series. 13 - 24.
44. Goetz Graefe, Haris Volos, Hideaki Kimura, Harumi Kuno, Joseph Tucek, Mark
Lillibridge, Alistair Veitch:
In-Memory Performance for Big Data. 37 - 48.
45. Fei Li, H. V. Jagadish: Constructing an Interactive Natural Language Interface for
Relational Databases. 73 - 84.
46. Chuanwen Li, Yu Gu, Jianzhong Qi, Ge Yu, Rui Zhang, Wang Yi:
Processing Moving kNN Queries Using Influential Neighbor Sets. 113 - 124.
47. Barzan Mozafari, Purna Sarkar, Michael Franklin, Michael Jordan, Samuel Madden:
Scaling Up Crowd-Sourcing to Very Large Datasets: A Case for Active Learning. 125 136.
48. Jana Giceva, Gustavo Alonso, Timothy Roscoe, Tim Harris:
Deployment of Query Plans on Multicores. 233 - 244.
49. Rebecca Taft, Essam Mansour, Marco Serafini, Jennie Duggan, Aaron J. Elmore,
Ashraf Aboulnaga, Andrew Pavlo, Michael Stonebraker:
E-Store: Fine-Grained Elastic Partitioning for Distributed Transaction Processing. 245 256.
50. Ahmed El-Kishky, Yanglei Song, Chi Wang, Clare R. Voss, Jiawei Han:
Scalable Topical Phrase Mining from Text Corpora. 305 - 316.
51. Wenbo Tao, Minghe Yu, Guoliang Li: Efficient Top-K SimRank-based Similarity
Join. 317 - 328.
52. Bogdan Alexe, Mary Roth, Wang-Chiew Tan: Preference-aware Integration of
Temporal Data. 365 - 376.
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53.Loc Do, Hady W. Lauw, Ke Wang: Mining Revenue-Maximizing Bundling
Configuration. 593 - 604.
54. Shiyu Yang, Muhammad Aamir Cheema, Xuemin Lin, Wei Wang:
Reverse k Nearest Neighbors Query Processing: Experiments and Analysis. 605 - 616.
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