Survey Paper
by on with No Comments

Week 1 (3/29):

  1. I have found a reasonable amount of papers to read.
  2. I have refined the topic. The previous topic was about analyzing and find the relationship between weather pattern and oil stock price. I have decided to broaden the topic to find the relationship between two general entities (so not just weather pattern and oil stock price) by developing an algorithm for similarity scoring and matching.
  3. I have a basic outline for the survey paper jotted down.

Week 2 (4/5):

  1. A lot of readings, especially about SVM (Support Vector Machine)
  2. Work on adding some more text in the introduction part
  3. Read, read, and read.
  4. Explore the term artificial neural networks, etc.

Week 3 (4/12):

  1. Read about different approach to pattern matching problem in other area of study (BLAST, etc.)
  2. Read about AI neural networks, it’s confusing.
  3. Start adding meat to the outline of the survey paper.

Week 4 (4/19):

  1. Watch the MIT’s Opencourseware Intro to AI
  2. Modular Neural Network – Reading
  3. SVM readings

Week 5 (4/26):

  1. Continue the course
  2. Re-learn calculus

Annotated Bibliographies
by on with No Comments
I/ Econ Simulation Game
1) “Educational Video Game Design: A Review of the Literature – Semantic Scholar.” N.p., n.d. Web. 16 Feb. 2017.
2) Squire, Kurt. “Changing the Game: What Happens When Video Games Enter the Classroom.” Innovate: journal of online education 1.6 (2005): n. pag. www.bibsonomy.org. Web. 16 Feb. 2017.
3) —. “Video Games in Education.” International Journal of Intelligent Simulations and Gaming 2 (2003): 49–62. Print.
II/ Social Network Data Mining
1) Cheong, France, and Christopher Cheong. “Social Media Data Mining: A Social Network Analysis Of Tweets During The 2010-2011 Australian Floods.” (2011): n. pag. works.bepress.com. Web. 16 Feb. 2017.
2) Kempe, David, Jon Kleinberg, and Éva Tardos. “Maximizing the Spread of Influence Through a Social Network.” Proceedings of the Ninth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. New York, NY, USA: ACM, 2003. 137–146. ACM Digital Library. Web. 16 Feb. 2017. KDD ’03.
3) Wu, X. et al. “Data Mining with Big Data.” IEEE Transactions on Knowledge and Data Engineering 26.1 (2014): 97–107. IEEE Xplore. Web.
III/ Connection between stocks
Zager, Laura A., and George C. Verghese. “Graph Similarity Scoring and Matching.” Applied Mathematics Letters 21.1 (2008): 86–94. ScienceDirect. Web.