INLS 490-154: Introduction to Information Retrieval System Design and Implementation

Fall 2008. Wednesdays 9:30am-12:15pm, Manning 214

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Selected Student Projects - Fall 2008
Video Game Review Database Search by Ben Pennell
Lemur as a Web Application by Philip Fulcher
Relevance Feedback with Query Term Suggestions by Kyle Richardson

Project Guidelines
As a part of this course, you are required to do a project demonstrating several of the concepts covered during the course. Before starting the actual project, you will be providing a proposal (details below), and upon the approval of the instructor, you can commence the project. This project will be due on December 7, 2008. Early submissions are encouraged. The project submission should be in form of (1) source files, (2) online working site, and (3) a report. The project will be tested with Firefox browser. Remember, the project carries 25% of the grade for this class.

Project proposal (Due: 10/22/2008)
You need to submit a brief article (2-4 pages) proposing the project that you want to do. This article should have
  • Problem description
  • Your approach/design
  • What is unique about your approach? In other words, if you're trying to sell this, why would anyone bother investing in this instead of using an off-the-shelf product?
  • Mockup and/or a brief description of what the outcome will be.
Final project (Due: 12/07/2008)
You are allowed to pick your application/domain. You can even use some existing project, but you need to specify how much is already done. Your final project MUST have the following components.
  • A text collection (unstructured data) of a "reasonable" size (preferably collected by a crawl).
  • A user interface with proper navigational tools so that even a naive user can utilize it with ease.
  • A search facility that allows one to perform full-text search in the collection.
  • A way to visualize the information (rank list, clusters, tag-cloud, etc.).
  • A mechanism to log all the user interactions.
  • At least one feature that is not commonly found in most "traditional" IR systems.
For text processing (mostly search-related), you are required to use Lemur. For structured databases, MySQL is recommended. For building UI, PHP is recommended.
You may optionally have
  • Advance search.
  • Dynamic UI to enhance user experience.
  • Interactive session support.
  • Meshing with a live Web application.
  • Clever use of CSS and Javascript for validation and site configuration.
  • Evaluation of processes/results with appropriate measures.
Finally, this should be the kind of work that you feel comfortable (and proud) demonstrating and listing on your portfolio. At the least, your project will be showcased (at your discretion) on the course website.
Your final submission should include all the source files (including the parameter files), a link to the online working site, and a brief article documenting the project. This document should have
  • Introduction - what is this project about and what it does/serves. (1/2 to 1 page)
  • Design details (may include figures). Explain your decisions behind certain design choices. (1-2 pages)
  • Usage scenario (may include screenshots). (1-3 pages)
  • Known issues and future work. (1-2 pages)
  • License.
Grade rubric
  • Proposal (15 points)
  • Source and parameter files (10 points)
  • Working site
    • Proper use of tools (10 points)
    • Ease of use of the interface (10 points)
    • Functionality (does it serve what it says in the proposal?) (10 points)
    • Features (10 points)
    • Explanation of processes and results (10 points)
  • Final report (25 points)
Project ideas
  • An interactive IR system that suggests related terms to the user based on the initial query. Based on the feedback from the user (the terms that he selects), the original query can be modified and run again.
  • An interactive IR system that shows related queries to the user based on the pre-stored or learned queries from the past.
  • A faceted browsing and searching system that allows one to browse through information content (text documents) based on various facets (category, author, date, etc.) as well as do full-text search.

| Chirag Shah | Last update: December 19, 2008 |