1. 1896192019872006 Data Mining with Big Data IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING, 2014 Xiangyu Cai （ 5120309687 ）

2. 1896192019872006 Why choose this paper? General introduction to big data characteristics Indicate the challenges with big data project Recommend references and related works to overcome the big data challenges

3. 1896192019872006 OUTLINE  Introduction  Big data characteristics: HACE Theorem  Data Mining Challenges with Big Data  Research Initiatives and Projects  Related Work  Conclusion

4. 1896192019872006 I. Big Data Characteristics

5. 1896192019872006 HACE Theorem Huge Data with Heterogeneous and Diverse Dimensionalities Autonomous Sources with Distributed and Decentralized Control Complex and Evolving Relationships

6. 1896192019872006 II. Data Mining Challenges with Big Data

7. 1896192019872006 Data Mining Challenges with Big Data Big Data Mining Platform Big Data Semantics and Application Knowledge Information Sharing and Data Privacy Domain and Application Knowledge Big Data Mining Algorithms Local Learning and Model Fusion for Multiple Information Sources Mining form Sparse, Uncertain and Incomplete Data Mining Complex and Dynamic Data

8. 1896192019872006 III. Related Research & Work

9. 1896192019872006 Data Mining Challenges with Big Data Big Data Mining Platform MapReduce Integration of R and Hadoop Big Data Semantics and Application Knowledge “Anonymizing Classification Data Using Rough Set Theory” User privacy restrictions may include: No local data copies or downloading All analysis must be deployed based on the existing data storage systems without violating existing privacy settings