Document Clustering for Natural Language Dialogue-based IR (Google for the Blind) Antoine Raux IR Seminar and Lab Fall 2003 Initial Presentation

Background Current search engines: user browses through an ordered list of retrieved documents Problem: for some users and/or some devices, this is not realistic –Speech only interaction (e.g. for the blind, phone-based systems) –Small devices (e.g. PDA, cell phones)

Goal Build a light-weight, “natural language” dialogue-based interface to refine queries and select relevant documents.

Previous Work Research on innovative interfaces for IR using clustering –e.g. Scatter/Gather Technology to enable the visually impaired to access the web –Page readers, web navigators But no research combining the two: –Using clustering to perform speech-based IR

Problem Definition Starts with a free query –“What are you seeking information about?” Turn-based interaction –System turns: 20 words at most –User turns: free, natural language Goal: retrieve one document

Baseline Solution Feed the initial query to a traditional search engine Read the first words of the top document and ask “Do you want this document?” If users says “No”, read the first words of the next document, and so on.

Proposed (Initial) Solution 1.Feed the initial query to a traditional search engine 2.Cluster the set of selected documents into a small number of cluster (e.g. 2-5) 3.Label each cluster 4.Generate a question to select a cluster 5.If small number of documents left, traverse the list sequentially else go back to step 2

Planned Implementation Use the Lemur Toolkit for parsing, indexing and basic retrieval Implement (in C++) a top-down clustering algorithm that labels each cluster Implement a (very simple) CGI user interface RetrievalClusteringQuestion Document Summaries

To be continued…