The DOI matches its Crossref record.
A patent search and classification system
Open accessAbstract
We present a system for searching and classifying U.S. patent documents, based on Inquery.Patents are distributed through hundreds of collections, divided up by general area.The system selects the best collections for the query.Users can search for patents or classify patent text.The user interface helps users search in fields without requiring the knowledge of Inquery query operators.The system includes a unique "phrase help" facility, which helps users find and add phrases and terms related to those in their query.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cited by
A Survey of Deep Active Learning
Ren, P., Xiao, Y., Chang, X., Huang, P.-Y., Li, Z., Gupta, B. B., Chen, X., & Wang, X. (2022) · ACM Computing Surveys · doi:10.1145/3472291 · Cited by 1,169
Topic based classification and pattern identification in patents
Venugopalan, S., & Rai, V. (2015) · Technological Forecasting and Social Change · doi:10.1016/j.techfore.2014.10.006 · Cited by 116
Metadata
- Authors
- Larkey, L. S.
- Venue
- Proceedings of the fourth ACM conference on Digital libraries
- Publisher
- ACM
- Published
- 1999-08
- Pages
- 179-187
- OpenAlex
- W2093098531
- Cited by
- 203
- References
- 0
- FWCI
- 4.16
- Type
- conference paper
- Language
- en
- Open access
- gold
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: A patent search and classification system. https://app.cochat.ai/papers/10.1145/313238.313304
- The paper
- Larkey, L. S. (1999). A patent search and classification system. Proceedings of the fourth ACM conference on Digital libraries. https://doi.org/10.1145/313238.313304
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
