DOE CODE   /    Search Results   /    Search tool plug-in: imploements latent topic feedback

Search tool plug-in: imploements latent topic feedback

RESOURCE

Publicly Accessible Repository
https://github.com/LLNL/iris
https://doi.org/10.11578/dc.20171025.1308

SAVE / SHARE



LLNL Badge

Abstract

IRIS is a search tool plug-in that is used to implement latent topic feedback for enhancing text navigation. It accepts a list of returned documents from an information retrieval wywtem that is generated from keyword search queries. Data is pulled directly from a topic information database and processed by IRIS to determine the most prominent and relevant topics, along with topic-ngrams, associated with the list of returned documents. User selected topics are then used to expand the query and presumabley refine the search results.
Release Date:
2011-09-22
Project Type:
Open Source, Publicly Available Repository
Software Type:
Scientific
Licenses:
GNU Lesser General Public License v3.0
Sponsoring Org.:
Code ID:
1941
Site Accession Number:
4799
Research Org.:
Lawrence Livermore National Laboratory
Country of Origin:
United States

RESOURCE

Publicly Accessible Repository
https://github.com/LLNL/iris
https://doi.org/10.11578/dc.20171025.1308

SAVE / SHARE



LLNL Badge

Citation Formats

Search tool plug-in: imploements latent topic feedback. Computer Software. https://github.com/LLNL/iris. USDOE. 22 Sep. 2011. Web. doi:10.11578/dc.20171025.1308.
(2011, September 22). Search tool plug-in: imploements latent topic feedback. [Computer software]. https://github.com/LLNL/iris. https://doi.org/10.11578/dc.20171025.1308.
"Search tool plug-in: imploements latent topic feedback." Computer software. September 22, 2011. https://github.com/LLNL/iris. https://doi.org/10.11578/dc.20171025.1308.
@misc{ doecode_1941,
title = {Search tool plug-in: imploements latent topic feedback},
author = ,
abstractNote = {IRIS is a search tool plug-in that is used to implement latent topic feedback for enhancing text navigation. It accepts a list of returned documents from an information retrieval wywtem that is generated from keyword search queries. Data is pulled directly from a topic information database and processed by IRIS to determine the most prominent and relevant topics, along with topic-ngrams, associated with the list of returned documents. User selected topics are then used to expand the query and presumabley refine the search results.},
doi = {10.11578/dc.20171025.1308},
url = {https://doi.org/10.11578/dc.20171025.1308},
howpublished = {[Computer Software] \url{https://doi.org/10.11578/dc.20171025.1308}},
year = {2011},
month = {sep}
}