LIPTUS: Associating Structured and Unstructured Information in a Banking Environment
Summary: LIPTUS links structured customer and account profiles with unstructured interactions (emails, transcribed calls) for unified analytics. Text-mining-derived interaction metadata enables cross-domain analytics with warehoused data, and the paper discusses deployment challenges in a large Indian bank. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
No non-self incoming citations found for this paper in this database.
Authors
- 1. M. Bhide (IBM)
- 2. A. Gupta (IBM)
- 3. R. Gupta (IBM)
- 4. P. Roy (IBM)
- 5. M. Mohania (IBM)
- 6. Z. Ichhaporia (Housing Development Finance Corporation Bank Limited)
BibTeX Citation
@inproceedings{bhide_sigmod07,
title = {{LIPTUS: Associating Structured and Unstructured Information in a Banking Environment}},
author = {Bhide, M. and Gupta, A. and Gupta, R. and Roy, P. and Mohania, M. and Ichhaporia, Z.},
series = {{SIGMOD} '07},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/1247480.1247587},
url = {https://dl.acm.org/doi/10.1145/1247480.1247587},
year = {2007}
}Incoming Citations (Sorted by Pagerank)
Showing 0 of 0 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|
Previous
Page 1 / 1
Next
Outgoing Citations (Sorted by Pagerank)
Showing 1 of 1 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 3,507 | Efficiently Linking Text Documents with Relevant Structured Information | 2006 | VLDB | 7.3574742e-05 |
Previous
Page 1 / 1
Next
Semantically Similar Papers
| # | Overall Rank | Paper | Year | Venue |
|---|---|---|---|---|
| 1 | 10,719 | Doctopus: A System for Budget-aware Structural Data Extraction from Unstructured Documents | 2025 | SIGMOD |
| 2 | 9,466 | LEAP: LLM-powered End-to-end Automatic Library for Processing Social Science Queries on Unstructured Data | 2025 | VLDB |
| 3 | 8,102 | Scalable Web Data Extraction for Online Market Intelligence | 2009 | VLDB |
| 4 | 11,980 | Building Structured Databases of Factual Knowledge from Massive Text Corpora | 2017 | SIGMOD |
| 5 | 14,210 | Mining Insurance Data at Swiss Life | 1997 | VLDB |
| 6 | 8,591 | A New Paradigm in Tuning Learned Indexes: A Reinforcement Learning Enhanced Approach | 2025 | SIGMOD |
| 7 | 5,933 | Exploiting Evidence from Unstructured Data to Enhance Master Data Management | 2012 | VLDB |
| 8 | 12,709 | One Platform for Mining Structured and Unstructured Data: Dream or Reality? | 2006 | VLDB |
| 9 | 3,507 | Efficiently Linking Text Documents with Relevant Structured Information | 2006 | VLDB |
| 10 | 12,169 | Mining Latent Entity Structures from Massive Unstructured and Interconnected Data | 2014 | SIGMOD |