Abstract:
Community Question Answering platforms have been trendy in recent times. These
are web-based information systems that connect users with similar interests. Stack
Overflow is one such forum popular among the software development community.
The website uses tagging as a strategy to categories question contents and connect
questions with the most expert users in particular technological domains. Currently,
the tagging feature operates as a manual process.
“StagIt” was implemented to eliminate the extra time and ambiguity from the
developer activity by automating the tagging process. The application is designed as
a Chrome plugin in the Stack Overflow website, and covers selected sub-domains of
C# technology.
The proposed solution obtains the question title and body from users and predicts
the tags on the fly. The system’s core leverages multi-label classification techniques
and TF-IDF feature extraction and LinearSVC machine learning algorithm.
