Using Trees to Depict a Forest
Summary: Replaces ranked top-k results with a page of diverse cluster representatives, shown preferable in a user study. A tree-based method efficiently generates and smoothly updates representatives under query refinement, outperforming prior approaches in quality and speed. (summarized by gpt-5.6-luna on Jul 24 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Bin Liu (University of Michigan)
- 2. H.V. Jagadish (University of Michigan)
BibTeX Citation
@article{liu_vldb09,
title = {{Using Trees to Depict a Forest}},
author = {Liu, Bin and Jagadish, H.V.},
journal = {PVLDB},
series = {{VLDB} '09},
doi = {10.14778/1687627.1687643},
url = {https://doi.org/10.14778/1687627.1687643},
year = {2009}
}Incoming Citations (Sorted by Pagerank)
Showing 5 of 5 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 1,807 | DisC Diversity: Result Diversification based on Dissimilarity and Coverage | 2013 | VLDB | 9.7054469e-05 |
| 6,893 | Skimmer: Rapid Scrolling of Relational Query Results | 2012 | SIGMOD | 5.7446791e-05 |
| 8,223 | Query Expansion Based on Clustered Results | 2011 | VLDB | 5.4631602e-05 |
| 8,485 | Diversity based Relevance Feedback for Time Series Search | 2014 | VLDB | 5.4155551e-05 |
| 10,831 | Holistic query Approximation via RL Modeling | 2025 | VLDB | 5.093636e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 9 of 9 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 5 | Optimal Aggregation Algorithms for Middleware [Extended Abstract] | 2001 | PODS | 0.0010828372 |
| 31 | BIRCH: An Efficient Data Clustering Method for Very Large Databases | 1996 | SIGMOD | 0.00050347119 |
| 304 | Automatic Subspace Clustering of High Dimensional Data for Data Mining Applications | 1998 | SIGMOD | 0.00021917388 |
| 351 | CURE: An Efficient Clustering Algorithm for Large Databases | 1998 | SIGMOD | 0.00020424271 |
| 4,222 | Density Biased Sampling: An Improved Method for Data Mining and Clustering | 2000 | SIGMOD | 6.8227421e-05 |
| 4,321 | Efficiently Answering Top-k Typicality Queries on Large Databases | 2007 | VLDB | 6.7617825e-05 |
| 5,774 | DataScope: Viewing Database Contents in Google Maps' Way | 2007 | VLDB | 6.0923864e-05 |
| 6,815 | Supporting Ranking and Clustering as Generalized Order-By and Group-By | 2007 | SIGMOD | 5.7652375e-05 |
| 9,710 | DataLens: Making a Good First Impression | 2009 | SIGMOD | 5.2343812e-05 |
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Semantically Similar Papers
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|---|---|---|---|---|
| 1 | 3,047 | Similarity Evaluation on Tree-structured Data | 2005 | SIGMOD |
| 2 | 6,832 | A Scalable Index for Top-k Subtree Similarity Queries | 2019 | SIGMOD |
| 3 | 9,710 | DataLens: Making a Good First Impression | 2009 | SIGMOD |
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| 5 | 10,153 | Faster Relational Algorithms Using Geometric Data Structures | 2026 | PODS |
| 6 | 1,327 | A Unified Approach to Ranking in Probabilistic Databases | 2009 | VLDB |
| 7 | 5,887 | Call to Order: A Hierarchical Browsing Approach to Eliciting Users' Preference | 2010 | SIGMOD |
| 8 | 1,526 | Ordering the Attributes of Query Results | 2006 | SIGMOD |
| 9 | 9,874 | Fast Search-By-Classification for Large-Scale Databases Using Index-Aware Decision Trees and Random Forests | 2023 | VLDB |
| 10 | 1,725 | Addressing Diverse User Preferences in SQL-Query-Result Navigation | 2007 | SIGMOD |