Idea navigation: structured browsing for unstructured text

Authors:
Robin Stewart;Gregory Scott;Vladimir Zelevinsky
Affiliations:
MIT, Cambridge, MA, USA;Tufts University, Medford, MA, USA;Endeca, Cambridge, MA, USA
Venue:
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Year:
2008

Citing 3
Cited 6

Finding the flow in web site search

Communications of the ACM
Introduction

Communications of the ACM - Supporting exploratory search
ESTER: efficient search on text, entities, and relations

SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval

Faceted exploration of image search results

Proceedings of the 19th international conference on World wide web
ImageSieve: exploratory search of museum archives with named entity-based faceted browsing

Proceedings of the 73rd ASIS&T Annual Meeting on Navigating Streams in an Information Ecosystem - Volume 47
Botanical data retrieval system supporting discovery learning

Proceedings of the 1st ACM International Conference on Multimedia Retrieval
Little search game: term network acquisition via a human computation game

Proceedings of the 22nd ACM conference on Hypertext and hypermedia
Semantics Discovery via Human Computation Games

International Journal on Semantic Web & Information Systems
A video navigation interface using multi-faceted search hierarchies

Proceedings of the 4th ACM Multimedia Systems Conference

Quantified Score

Hi-index	0.01

Visualization

Abstract

Traditional interfaces for information access do not fully support queries that rely on semantic relationships between terms. To better support such queries, we introduce a system that automatically extracts subject-verb-object concepts from unstructured text documents and dynamically presents them to the user as navigable refinements. This approach, which we call "idea navigation," makes subject-verb-object querying as simple as selecting successive refinements. It also supports exploratory search by providing a view of the most common ideas in the current result set. First-time users of a prototype system successfully used idea navigation to solve realistic search tasks, demonstrating its effectiveness.