Personalized Assistance System

A researcher, from Penn State, has been working on a personalized assistance system that automatically helps users find more relevant search results (see the article).

Stages of Knowledge Discovery in Websites

                                          |------------------
                     |--------------------| 3. PERSONALIZATION
|---------------------| 2. Advanced Web Mining
| 1. Clickstream Analysis

Personalization Companies

Rule-based Personalization:
ATG, BroadVision, Epiphany, Blue Martini

Collaborative Filtering Personalization:
Amazon.com

Statistical Modeling:
Touch Clarity

State-based Personalization:
Xamplify

Web Mining Research Links by Tingshao Zhu

Social Network Analysis

The Oracle of Bacon

Erdös Number Project

Six Degrees of Separation Experiment

ReferralWeb

Scale-Free Networks

Most social networks including the Web seem to be scale-free networks. A Scale-free network is unique because a small number of nodes are highly connected (e.g., the majority of nodes are sparsely connected).

Wikipedia Encyclopedia

Data Mining Researchers

Rakesh Agrawal
Surajit Chaudhuri
Umesh Dayal
Max J. Egenhofer
Usama Fayyad (Microsoft)
Christophe Giraud-Carrier
Jiawei Han
Daniel Keim
Hans-Peter Kriegel
Yike Guo
Laks V.S. Lakshmanan
Hongjun Lu
Alberto Mendelzon
Raymond T. Ng
Tamer Ozsu
Rajeev Rastogi
Ken Ross
Sunita Sarawagi
Wei-Min Shen
Kyuseok Shim
Avi Silberschatz
Matt Smith
Jaideep Srivastava
Philip S. Yu
Clement Yu
Jeffrey D. Ullman
Ke Wang
Osmar Zaiane

24 Key Database Marketing Techniques

This article is a good overview of 24 marketing methods which are useful in determining what data should be collected in order to personalize a website.

Collaborative Filtering Resources

Collaborative Filtering (Berkeley)

Data Mining Resources

Data Mining Resources (@ www.scd.ucar.edu)

Data Mining Resources (@ www.cs.purdue.edu)

Data Mining Resources (Zillman's List)

Knowledge Discovery Approaches

Data Mining enables us to automatically sift through mass amounts of data to discover KNOWLEDGE. A couple popular approaches are summarized below:

Identify customer groups and forecast their behaviour. This is commonly used in Marketing, fraud detection, and more and more frequently on the web for various purposes.

Market basket analysis: "If customer bought product P, he or she
is likely to buy product Q and R" (Amazon.com uses this approach)

Personalization Papers & Links

Data Mining for Web Intelligence (PDF)
Integrating Web Usage and Content Mining for More Eective Personalization (PDF)
WebData Mining (DePaul University)
AutomaticPersonalization Based on Web Usage Mining
Semantic WebPersonalization
Links& White Papers

Website Log Analyzers

AWStats | Comparison to the below Log analyzers
Analog
Webalizer

Web Log Analysis Tools
There are several free log analysis tools. AWStats seems to be the most popular open source tool, however, I'm not sure if it is as nice as some of the commercial products such as Omniture's SiteCatalyst.

Information Retrieval

This is a good reference book with commonly used information retrieval methods.

Personalized News and Blog Site

Here is new personalization website,
which is done quite well. It is called href="http://findory.com/">Findory. It is smart because no login
is required yet personalization occurs from the moment you visit
the site and begin clicking.



Geeking
with Greg is a blog that discusses personalization and
customization in web search and online news.

Data Mining Interest Continues To Rise

University
leads data mine plan (NEWS.com.au - Australia)

"The University of Technology Sydney is trying to establish a $38
million data mining center of excellence to involve universities,
industry and government..."

It is interesting to see how important Data Mining is becoming.