dc.contributor.author |
Madeti, Preetham |
en_US |
dc.date.accessioned |
2016-11-03T17:40:50Z |
|
dc.date.accessioned |
2019-09-08T02:58:50Z |
|
dc.date.available |
2016-11-03T17:40:50Z |
|
dc.date.available |
2019-09-08T02:58:50Z |
|
dc.date.issued |
2016 |
|
dc.identifier |
959555447 |
en_US |
dc.identifier.other |
b22150444 |
en_US |
dc.identifier.uri |
http://hdl.handle.net/1989/11971 |
|
dc.description |
x, 27 leaves : illustrations ; 29 cm |
en_US |
dc.description.abstract |
Monitoring posts quality on the Stack Overflow website is of critical importance to make the experience smooth for its users. It strongly disapproves unproductive discussion and un-related questions being posted. Questions can get closed for several reasons ranging from questions that are un-related to programming, to questions that do not lead to a productive answer. Manual moderation of the site's content is a tedious task as approximately seventeen thousand new questions are posted every day. Therefore, leveraging machine learning algorithms to identify the bad questions would be a very smart and time-saving method for the community. The goal of this thesis is to build a machine learning classifier that could predict if a question will be closed or not, given the various textual and post related features. A training model was created using Apache Spark's Machine Learning Libraries. This model could not only predict the closed questions with good accuracy, but computes the result in a very small time-frame. |
en_US |
dc.description.statementofresponsibility |
by Preetham Madeti. |
en_US |
dc.language.iso |
en_US |
en_US |
dc.subject.lcsh |
Computer programming--Electronic discussion groups. |
en_US |
dc.subject.lcsh |
Machine learning. |
en_US |
dc.subject.lcsh |
Computer science. |
en_US |
dc.title |
Using Apache Spark's MLlib to predict closed questions on Stack overflow |
en_US |
dc.type |
Thesis |
en_US |