Improving Topic Model Stability for Effective Document Exploration

Simple item page
dc.contributor.authorYang, Yi
dc.contributor.authorPan, Shimei
dc.contributor.authorSong, Yangqiu
dc.contributor.authorLu, Jie
dc.contributor.authorTopkara, Mercan
dc.date.accessioned2020-03-05T17:49:06Z
dc.date.available2020-03-05T17:49:06Z
dc.descriptionProceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence (IJCAI-16)en_US
dc.description.abstractTopic modeling has become a ubiquitous topic analysis tool for text exploration. Most of the existing works on topic modeling focus on fitting topic models to input data. They however ignore an important usability issue that is closely related to the end user experience: stability. In this study, we investigate the stability problem in topic modeling. We first report on the experiments conducted to quantify the severity of the problem. We then propose a new learning framework to mitigate the problem by explicitly incorporating topic stability constraints in model training. We also perform user study to demonstrate the advantages of the proposed method.en_US
dc.description.urihttps://www.ijcai.org/Proceedings/16/Papers/635.pdfen_US
dc.format.extent5 pagesen_US
dc.genreconference papers and proceedingsen_US
dc.identifierdoi:10.13016/m2zmls-0dbk
dc.identifier.citationYang, Yi; Pan, Shimei; Song, Yangqiu; Lu, Jie; Topkara, Mercan; Improving Topic Model Stability for Effective Document Exploration; Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence (IJCAI-16); https://www.ijcai.org/Proceedings/16/Papers/635.pdfen_US
dc.identifier.urihttp://hdl.handle.net/11603/17493
dc.language.isoen_USen_US
dc.relation.isAvailableAtThe University of Maryland, Baltimore County (UMBC)
dc.relation.ispartofUMBC Information Systems Department Collection
dc.relation.ispartofUMBC Faculty Collection
dc.rightsThis item is likely protected under Title 17 of the U.S. Copyright Law. Unless on a Creative Commons license, for uses protected by Copyright Law, contact the copyright holder or the author.
dc.subjecttopic modeling
dc.subjecttext exploration
dc.subjecttext exploration
dc.subjectstability problem in topic modeling
dc.titleImproving Topic Model Stability for Effective Document Explorationen_US
dc.typeTexten_US

Files

License bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
2.56 KB
Format:
Item-specific license agreed upon to submission
Description:
Download

Collections

UMBC Information Systems Department
UMBC Faculty Collection