Dialogue and Information Retrieval
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Transcript Dialogue and Information Retrieval
Dialogue and Information Retrieval
Dialogs on Dialogs
March all the way through April 2003
Intersections between
Dialog Systems and IR
Current work
Call Routing
Question Answering
Why so little?
What else? Let’s brainstorm!
Call Routing
Task: given a NL expression of a problem,
classify (route) it in one of several
categories
Examples
AT&T: How May I Help You
British Telecom
Jennifer Chu-Carroll
Call Routing (2)
It’s a classification problem!
Salience (co-ocurrence) based
approaches (AT&T)
IR-like approaches (J. Chu-Carroll)
Treat user requests as “documents”
Use VSM and cosine similarity to classify
The IR in Call Routing
Regard the problem as text classification
Do standard IR work:
LSA
LDA
Centroid vs. KNN approaches
Results? Classification perf?
The Dialog in Call Routing
Disambiguation
Follow-up dialog
Easy to do based on the VSM IR approach
HMIHY: frame-based follow-up dialogs
Q: Is Call Routing dialog management?
Q: Or is it more like understanding?
Q: Why typical understanding/DM
approaches fail in HMIHY-type domains?
Question Answering
Task: answer to a question in Natural
Language from a database of documents
in Natural Language.
Examples:
http://www.ai.mit.edu/projects/infolab/
http://www.ask.com
IR in Question Answering
Everywhere:
Document indexing
Retrieval
…
What is different from traditional IR?
Some parsing/understanding of questions and
documents
Some language generation (?)
Dialog in QA
Refining the question:
Clarification dialogue
Decide which question to ask
Only for very restricted domains uses
fixed frames (Rutgers: HITIQA)
Why so little?
Different issues:
IR = lots of unstructured data, no NLP
Dialog = structured data, lots of NLP
Main problems:
Structural mismatch
NLU mismatch
But HUGE potential!
Voice-only random access to large
amounts of information (“Voice IR”):
technical manuals of “in-the-field” devices
(e.g. NASA)
tutorial systems
phone-based Google (e.g. legal information…)
GUI+ for IR
Learn dialog stuff from data (LM, NLG,
parsing…)