Managing General and Individual Knowledge in Crowd Mining Applications
Summary: Architecture integrating general (ontologies/DB) and individual (crowd habits/preferences) knowledge for mixed reasoning, automatic task generation, and result analysis. Uses it to compare/extend crowdsourcing systems, highlight research challenges, and demonstrate reuse with OASSIS. (summarized by gpt-5-mini on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Yael Amsterdamer (Tel Aviv University)
- 2. Susan B. Davidson (University of Pennsylvania)
- 3. Anna Kukliansky (Tel Aviv University)
- 4. Tova Milo (Tel Aviv University)
- 5. Slava Novgorodov (Tel Aviv University)
- 6. Amit Somech (Tel Aviv University)
BibTeX Citation
@inproceedings{amsterdamer_cidr15,
address = {Amsterdam, Netherlands},
series = {{CIDR} '15},
title = {{Managing General and Individual Knowledge in Crowd Mining Applications}},
booktitle = {Proceedings of the {Conference} on {Innovative} {Data} {Systems} {Research}},
author = {Amsterdamer, Yael and Davidson, Susan B. and Kukliansky, Anna and Milo, Tova and Novgorodov, Slava and Somech, Amit},
year = {2015}
}Incoming Citations (Sorted by Pagerank)
Showing 3 of 3 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 7,505 | Crowdsourced Data Management: Overview and Challenges | 2017 | SIGMOD | 5.5057737e-05 |
| 7,889 | Subjective Knowledge Base Construction Powered By Crowdsourcing and Knowledge Base | 2018 | SIGMOD | 5.4312213e-05 |
| 7,954 | A Natural Language Interface for Querying General and Individual Knowledge | 2015 | VLDB | 5.4182701e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 11 of 11 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 92 | CrowdDB: Answering Queries with Crowdsourcing | 2011 | SIGMOD | 0.00034670735 |
| 257 | Crowdsourced Databases: Query Processing with People | 2011 | CIDR | 0.00022958404 |
| 433 | Corleone: Hands-Off Crowdsourcing for Entity Matching | 2014 | SIGMOD | 0.00018324965 |
| 514 | Data Curation at Scale: The Data Tamer System | 2013 | CIDR | 0.00016999652 |
| 1,926 | Counting with the Crowd | 2013 | VLDB | 9.3636304e-05 |
| 2,260 | Chimera: Large-Scale Classification using Machine Learning, Rules, and Crowdsourcing | 2014 | VLDB | 8.7320885e-05 |
| 2,653 | CrowdFill: Collecting Structured Data from the Crowd | 2014 | SIGMOD | 8.1693619e-05 |
| 2,832 | Crowd Mining | 2013 | SIGMOD | 7.9554419e-05 |
| 3,839 | Optimal Crowd-Powered Rating and Filtering Algorithms | 2014 | VLDB | 6.9896853e-05 |
| 5,000 | Descriptive and Prescriptive Data Cleaning | 2014 | SIGMOD | 6.3194405e-05 |
| 7,230 | OASSIS: Query Driven Crowd Mining | 2014 | SIGMOD | 5.5779439e-05 |
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Semantically Similar Papers
| # | Overall Rank | Paper | Year | Venue |
|---|---|---|---|---|
| 1 | 7,954 | A Natural Language Interface for Querying General and Individual Knowledge | 2015 | VLDB |
| 2 | 7,789 | Pushing the Boundaries of Crowd-enabled Databases with Query-driven Schema Expansion | 2012 | VLDB |
| 3 | 12,410 | NL2CM: A Natural Language Interface to Crowd Mining | 2015 | SIGMOD |
| 4 | 3,173 | Truth Inference in Crowdsourcing: Is the Problem Solved? | 2017 | VLDB |
| 5 | 5,615 | CrowdQ: Crowdsourced Query Understanding | 2013 | CIDR |
| 6 | 7,505 | Crowdsourced Data Management: Overview and Challenges | 2017 | SIGMOD |
| 7 | 5,470 | Crowdsourcing Applications and Platforms: A Data Management Perspective | 2011 | VLDB |
| 8 | 2,832 | Crowd Mining | 2013 | SIGMOD |
| 9 | 9,459 | Ontology Assisted Crowd Mining | 2014 | VLDB |
| 10 | 7,230 | OASSIS: Query Driven Crowd Mining | 2014 | SIGMOD |