1. Seattle Event Finder Justin Meyer Jessica Leung Jennifer Hanson
Sophia Gansky
Chuan Yu

2. Goal
Create a specialized search engine for events in the Seattle area.
Enable search by
Location
Date and Time
Price
Category
Enable full-text search

3. The Internet
Nutch Crawler
Event Extraction
Event Indexing
Geocoding
Event Database
Web Service
Event Classification
Web Application

4. Reality
Site-specific extractors used rather than machine learning approach
Classifier is tuned for the events from specifically chosen websites rather than the full web. (overfitted, but in a good way)
notifications not implemented.
Less dynamic web interface.

5. Demo
u:1987/eventfinder/search/

6. What We Found Surprising
CRF++ limited in extracting attributes
CRF extracts multiple values for one attribute from an event description
If only extract from a paragraph of description, in most cases, some attribute are not contented in.
Use Site-specific structures
Extracted attributes values from corresponding Html tags
No more ambiguity
Can extract all the attributes from the each event page
Javascript's negative impact
Some sites not fully loading after the first Http Request
URLs generated by Javascript functions could not be retrieved

7. Classifier Experiments
Variables / Results
Number of Categories: 8
Training Data Source: Crawler Data
Scaled vs. Non-scaled Training Data: Scaled
Single Words vs. Word Pairs as attributes: Single Words Only
Scaled LIBSVM attribute values? Yes
Lower Bound: 0
Upper Bound: 1
Weights
URL Words: 50
Title Words: 15
Location Words: 10
Tests (32 Recorded Tests)
Ablation: Turning On/Off features
Tuning: Adjusting Variable Values

8. Usability Experiment Survey Results
Participants went to the website and completed 3 tasks
Task completion and overall feedback
Only three submissions due to server load
Results
All found site navigable
Participants used list view, map view and individual event pages
Some results not relevant
Task 1: Find any event that is happening in Seattle Task 2: Find a music event that is happening more than a week away from now in Seattle Task 3: Find the celebration event of author Sandra Cisneros this past May (2009)
500/10,000
.5 task completion rate

9. What We Learned Information Retrieval / Extraction/Indexing:
Gained more experience with regex, Java servlet technology, and working with open-source projects.
Classifier:
Many methods of classification and related variables. Deciding on a classification method and setting variables can be as much of an art form as a science.
Front End:
Frameworks (Django) are very powerful but it takes a long time to learn. Watch your resources!

10. Breakdown of Work Justin - Classifier and Database
Jessica and Jenn - Front end
Sophia - Extraction, Nutch, Lucene, Database
Chuan - Extraction

11. Questions?