1. A Web-based Question Answering System Yu-shan & Wenxiu 03.08.2005

2. Outline System Architecture Query Expansion Pattern Learning Answering Extraction Performance & Evaluation

3. Our QA Massive web documents based – how to eliminate noise… Question classification – Focus on LOC –(LOC:city, LOC:country, LOC:state, LOC:other…) Multiple Query Expansion Suffix tree to aid surface pattern learning Use Regular Expression to extract answer

4. System Architecture

5. Question Expansion No expansion Delete question words & stop words –Save more space for expansion WordNet Synonym Expansion –Word ambiguous Dependency-based Word Similarity Expansion –Prof. Lin@Univ. of Alberta –http://www.cs.ualberta.ca/~lindek/demos/depsim.htm

6. Question Expansion Example Question: –What is the largest city in the world? Primary keywords: –is largest city world WordNet expansion: –is largest city world be metropolis human race Similarity expansion: –is largest city world doing town region

7. Suffix Tree Construct a general suffix tree for the top 100 snippets –each node has an index of the sentences it appears. –Set threshold N, pick up the longest common substrings which appear in more than N sentence, use them as candidate answers. –Manually filtering correct candidate answers to construct patterns Huge Noise… –Query keywds, common words, part of phrases… –Laborious manual work…

8. LOC:city Patterns is,, ….., is, ……, is, ……,

9. Answer Extraction Regular Expression Match Known_city_list filtering… –Contains 4682 cities… Direct pick out citynames from snippet Combine two approaches DEMO TIME

10. Answers from Google What is the largest city in the world? TREC answer: Tokyo Our answer: –Seoul –Memphis –Tokyo –Mexico City –Los Angeles Google snippet: “With a population of more than 10.2 million, Seoul, the capital of South Korea, is the world?s largest city in terms of population.” “…… we see that Memphis remained the largest city in the world from at least 3100 BCE to 2240 BCE”

11. Evaluation Use TREC-10 Labeled Questions ORIGPRIMWNSIM MRR0.750.60.470.52 PropCor rect 0.8 0.60.5