Web searches provide large amounts of information about web users. Data mining techniques can be used to analyze this information and create web user profiles. A key application of this approach is in marketing and offering personalized services, an area referred to as "data gold rush". The aim of this project is to develop a system that can be used to develop an intelligent web browser. This project focuses on the use of Decision Tree learning to create models of web users.
The power and usefulness of artificial neural networks have been demonstrated in several applications including speech synthesis, diagnostic problems, medicine, business and finance, robotic control, signal processing, computer vision and many other problems that fall under the category of pattern recognition. The goal of this project is to develop a character recognition system based on a neural network model.
The N-puzzle game provides a good framework for illustrating conceptual AI search in an interesting and motivating way. The objective of this project is to introduce the student to Analytical (Explanation-Based) Learning using the classical AI framework of search. Hands-on experiments with search algorithms combined with an Explanation Based Learning (EBL) component give students a deep, experiential understanding of the basics of EBL.
The jeopardy dice game Pig is very simple to describe, yet the optimal policy for play is far from trivial and was only recently solved. Using the computation of the optimal solution as a central challenge problem, we give the student a deep, experiential understanding of dynamic programming and value iteration through explanation, implementation examples, and implementation exercises.
Along with search engines, topic directories are the most popular sites on the Web. Topic directories organize web pages in a hierarchical structure according to their content. The aim of the project is to investigate the process of tagging web pages using the topic directory structures and apply Machine Learning techniques for automatic tagging. This would help in filtering out the responses of a search engine or ranking them according to their relevance to a topic.
The popular board game Clue serves as a fun focus problem for this introduction to propositional knowledge representation and reasoning. After covering fundamentals of propositional logic, students first solve basic logic problems with and without the aid of a satisfiability solver. Students then represent the basic knowledge of Clue in order to solve a Clue mystery. Could the current best stochastic SAT solver, Adaptive Novelty+, benefit from machine learning elements.