Collaborative Hierarchical Clustering in the Browser for
Scatter/Gather on the Web
Weimao Ke and Xuemei Gong
Laboratory for Information, Network & Computing Studies
College of Information Science and Technology
Drexel University, 3141 Chestnut St, Philadelphia, PA 19104
Scatter/Gather is a powerful browsing model for exploratory information seeking. However, its potential on the web scale has not been demonstrated due to
scalability challenges of interactive clustering. We have
developed in previous research a two-stage method to
support on-the-ﬂy Scatter/Gather, in which an oﬄine
module pre-computes a hierarchical structure to support constant time on-line interaction. In this work, we focus on the oﬄine hierarchy construction and develop
text clustering, Scatter/Gather, distributed computing,
can be conducted without explicit query speciﬁcation
(Cutting et al., 1992). Based on iterative user selection
and interactive text clustering, Scatter/Gather oﬀers
a powerful tool for navigating a large, complex information space. It enables the user to explore inherent associations among documents and topics in the data,
supporting learning and investigation (Hearst and Pedersen, 1996). However, major challenges associated with clustering
eﬃciency and scalability have hindered the adoption of
Scatter/Gather in IR practice. In particular, many clustering algorithms are computationally complex. Even eﬃcient classic methods such as k-means are of linear
time complexity, far from eﬃcient to support on-the-ﬂy
clustering on a large number of documents. The use of
Scatter/Gather for web browsing is desirable but practically challenging because of the web’s scale and dynamics. Until we can properly address these challenges, real-world applications of Scatter/Gather are unlikely
Notwithstanding its great potential in interactive IR,
Scatter/Gather research has so far focused on rather
small data collections. Its eﬃciency and eﬀectiveness on the web scale remain unaddressed. The research aims
to study scalable approaches to interactive clustering.
A major objective is to identify a scalable clustering architecture that can support Scatter/Gather interactions on the evolving web. Ultimately this will lead to new
development of web browsing techniques.
Information retrieval (IR) systems such as web search
engines play important roles in connecting people with
information. While searching is a widely accepted approach to ﬁnding information, browsing represents another basic IR paradigm. Among classic browsing models, Scatter/Gather is a unique approach in which searches
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Scatter/Gather is a highly interactive model for collection browsing and information retrieval based on text clustering (Cutting et al., 1992). It supports progressive
query speciﬁcation through user-system interaction and
clustering. In each Scatter/Gather iteration, the system
presents to the user a set of clusters (topical groups
of documents) in the information collection. The user
then picks one or...
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