Andreas Weigend
Stanford University
Stat 252 and MS&E 238
Class time Spring 2007: Monday 3:15 -6:05 pm
Class location Spring 2007: Gates B03

Data Mining and Electronic Business


This course is about People and Data: Collecting data about behavior on the web, in communication patterns, in social networks, on dating sites, etc. Mining the data, building predictive models, creating (and rejecting) hypotheses, designing cool experiments, and learning from them quickly. And figuring out what is similar to the past and what has changed, and what the underlying drivers are.

We will discuss the impact of this communication and data revolution on individuals, business, and society, essentially to most aspects of the world we live in. Applications range from online marketing (behavioral targeting and situational targeting) to architectures leveraging collective intelligence. We are also fortunate to have some great guest speakers come to class. The detailed content of each class of this year is on the course wiki, and some previous years are on the web (2005, 2004).

The first half of the quarter focuses on data: Click data (what all can be collected and what it is useful for), intention data (such the queries from the searches you do, we will also discuss social search), attention data (such as tags on social bookmarking sites with its important application for discovery), and interaction data (of email headers and social networking sites). The second half of the quarter focuses on models and on creating appropriate structures and incentives. We will discuss models for products (recommender systems), people (reputation systems), situation and location. We will also discuss collective intelligence, prediction markets.

Students are expected to actively engage in class discussions, to have their assumptions challenged, and to bring their various backgrounds to class in order to make it a great experience for themselves and everybody else.

Schedule : We meet once a week, on Monday afternoons for 3 hours each (Apr 9, 16, 23, 30, May 7, 14, 21, June 4, and once during exam week). The purpose is to make it really easy for everybody to physically come to class and participate. This is a lot more fun than just watching it on the internet, and you learn a lot more. Note that this explicitly includes SCPD students who only signed up for remote access, just don't tell anyone :)

Course wiki : All students have full read/write access to the course wiki at aweigend.wiskispaces.com. I encourage you to really actively contribute -- the class and you will benefit.

Grading : The main goal is that you get insights in the area of People and Data, and that you transfer them to your area, hopefully coming up with some interesting ideas and applications. To support this objective, your grade will be determined by the following:

  • Class w iki: We will form 8 groups, each with around 5 students. Each group is responsible to create the initial wikipage for one of the classes by Friday 6pm (i.e., 4 days after class). [30%]

  • Homeworks: There will be weekly assignments. The first 3 focus on hands-on experience with data (looking at web logs, using APIs, running an online advertising campaign, writing a discovery recommendation system for del.icio.us), the remaining ones focus on the readings and concepts. Homeworks are due the day before class at 5pm, such that we can look through them and give brief feedback in a timely manner. [50%]

  • Class participation. [20%]

  • Project: If you have a good and solid idea for an interesting project, I am happy to give feedback and jointly decide on whether it makes sense to do the project. I encourage projects in small groups. [optional]

There are also intership opportunities available ranging from San Francisco (Hitwise, web measurement) to Bangkok (Agoda, online travel), China and Singapore.

Readings:

Teaching Assistants:

  • Rudy Angeles
    Room 206 Sequoia Hall
    Office hors: Fri 2:30 - 4:00 (also via Yahoo messenger: stat252spring2007)
    rangeles@stanford.edu
    (650) 725-6148

  • Zehao Chen
    Room 238 Sequoia Hall
    Office hours: Mon 1:15 - 2:45
    zhchen@stanford.edu
    (650) 725-5952

Note: The previous version of this page (addressing students considering taking the course) is here.

http://www.weigend.com/Teaching/Stanford/index.html
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