Paper: Combining Text And Heuristics For Cost-Sensitive Spam Filtering

ACL ID W00-0719
Title Combining Text And Heuristics For Cost-Sensitive Spam Filtering
Venue International Conference on Computational Natural Language Learning
Session Main Conference
Year 2000
Authors

Spam filtering is a text categorization task that shows especial features that make it interest- ing and difficult. First, the task has been per- formed traditionally using heuristics from the domain. Second, a cost model is required to avoid misclassification of legitimate messages. We present a comparative evaluation of several machine learning algorithms applied to spam fil- tering, considering the text of the messages and a set of heuristics for the task. Cost-oriented biasing and evaluation is performed.