FeedMe: a collaborative alert filtering system (2006)
| Venue: | In Proceedings of the 2006 20th Anniversary Conference on Computer Supported Cooperative Work |
| Citations: | 4 - 2 self |
BibTeX
@INPROCEEDINGS{Sen06feedme:a,
author = {Shilad Sen and Werner Geyer and Michael Muller and Marty Moore and Beth Brownholtz and Eric Wilcox and David R Millen},
title = {FeedMe: a collaborative alert filtering system},
booktitle = {In Proceedings of the 2006 20th Anniversary Conference on Computer Supported Cooperative Work},
year = {2006},
pages = {89--98},
publisher = {ACM Press}
}
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Abstract
As the number of alerts generated by collaborative applications grows, users receive more unwanted alerts. FeedMe is a general alert management system based on XML feed protocols such as RSS and ATOM. In addition to traditional rule-based alert filtering, FeedMe uses techniques from machine-learning to infer alert preferences based on user feedback. In this paper, we present and evaluate a new collaborative naïve Bayes filtering algorithm. Using FeedMe, we collected alert ratings from 33 users over 29 days. We used the data to design and verify the accuracy of the filtering algorithm and provide insights into alert prediction. Categories and Subject Descriptors H.5.3 [Group and Organization Interfaces]: Collaborative
