Semi-structured information sharing systems are gaining in popularity because they allow users to easily create shared collections of textual documents, organized by a common set of fields. Unfortunately, in a large organization this freedom can result in an unwieldy space of shared information that is difficult to retrieve.
Standard tools like full-text search do not alleviate the problem, in part because they do not make any use of the structure within each document collection. In this paper, we describe an approach that goes beyond full-text search by taking advantage of both the structure of the document collections and a knowledge of what information types are important within the organization sharing the information.
We present an implemented indexing/browsing system called Notes Explorer that allows users to browse for entities (companies, people, etc.) across a large semi-structured information space. Notes Explorer incorporates three key components:
(1) automatic classification of document fields to recognize common entity and document collection types;
(2) entity-based browsing over multiple document collections, with type-dependent normalization;
(3) content-based filtering of browse results.