DBScholar

Back to papers

Supporting Keyword Search in Product Database: A Probabilistic Approach

Summary: Proposes a probabilistic, query-generation model for keyword search over structured product specs to bridge vocab gap with user queries. Ranks entities by P(query|entity) using MLE/MAP from specs, reviews, and logs; shows significant gains and enables facet/review annotation. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
10853
Venue
VLDB
Year
2013
Pagerank
5.871262e-05
Overall Rank
6,466 | 55.64%
DOI
10.14778/2556549.2556562

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{duan_vldb13,
        title = {{Supporting Keyword Search in Product Database: A Probabilistic Approach}},
        author = {Duan, Huizhong and Zhai, ChengXiang and Cheng, Jinxing and Kumar, Rohit},
        journal = {PVLDB},
        series = {{VLDB} '13},
        volume = {6},
        number = {14},
        pages = {1786--1797},
        doi = {10.14778/2556549.2556562},
        url = {https://doi.org/10.14778/2556549.2556562},
        year = {2013}
}

Incoming Citations (Sorted by Pagerank)

Showing 3 of 3 citing papers.

Rank Citing Paper Year Venue Pagerank
3,015 Organizing Data Lakes for Navigation 2020 SIGMOD 7.848843e-05
11,463 Approximating Probabilistic Group Steiner Trees in Graphs 2023 VLDB 5.093636e-05
12,128 ConfSeer: Leveraging Customer Support Knowledge Bases for Automated Misconfiguration Detection 2015 VLDB 5.093636e-05
Previous Page 1 / 1 Next

Outgoing Citations (Sorted by Pagerank)

Showing 7 of 7 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