Track: Search
Paper Title:
Compare&Contrast: Using the Web to Discover Comparable Cases for News Stories
Authors:
Abstract:
Comparing and contrasting is an important strategy people employ to
understand new situations and create solutions for new problems.
Similar events can provide hints for problem solving, as well as larger
contexts for understanding the specific circumstances of an event.
Lessons can be learned from past experience, insights can be gained
about the new situation from familiar examples, and trends can be
discovered among similar events. As the largest knowledge base for
human beings, the Web provides both an opportunity and a challenge
to discover comparable cases in order to facilitate situation analysis
and problem solving. In this paper, we present Compare&Contrast,
a system that uses the Web to discover comparable cases for news
stories, documents about similar situations but involving distinct
entities. The system analyzes a news story given by the user and
builds a model of the story. With the story model, the system
dynamically discovers entities comparable to the main
entity in the original story and uses these comparable entities as
seeds to retrieve web pages about comparable cases. The system is domain
independent, does not require any domain-specific knowledge
engineering efforts, and deals with the complexity of unstructured
text and noise on the web in a robust way.
We evaluated the system with an experiment on a
collection of news articles and a user study.
