DBScholar

Back to papers

An Efficient Publish/Subscribe Index for E-Commerce Databases

Summary: Efficient in-memory pub/sub index for high-dimensional, sparse e-commerce data; scales with subscriptions, event rate, and attribute variety. Extensible to prefix/suffix filtering and regex; achieves orders-of-magnitude faster construction, low memory, and efficient matching on AOL and Ebay datasets. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
11127
Venue
VLDB
Year
2014
Pagerank
5.7517379e-05
Overall Rank
6,861 | 52.93%
DOI
10.14778/2732296.2732299

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{zhang_vldb14,
        title = {{An Efficient Publish/Subscribe Index for E-Commerce Databases}},
        author = {Zhang, Dongxiang and Chan, Chee-Yong and Tan, Kian-Lee},
        journal = {PVLDB},
        series = {{VLDB} '14},
        volume = {7},
        number = {8},
        pages = {613--624},
        doi = {10.14778/2732296.2732299},
        url = {https://doi.org/10.14778/2732296.2732299},
        year = {2014}
}

Incoming Citations (Sorted by Pagerank)

Showing 4 of 4 citing papers.

Previous Page 1 / 1 Next

Outgoing Citations (Sorted by Pagerank)

Showing 15 of 15 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Previous Page 1 / 1 Next

Semantically Similar Papers