QFRecs - Recommending Features in Feature-Rich Software based on Web Documentation
| dc.contributor.author | Khan, Md Adnan Alam | |
| dc.contributor.examiningcommittee | Wang, Yang (Computer Science) Morrison, Jason (Biosystems) | en_US |
| dc.contributor.supervisor | Bunt, Andrea (Computer Science) | en_US |
| dc.date.accessioned | 2015-06-04T19:52:07Z | |
| dc.date.available | 2015-06-04T19:52:07Z | |
| dc.date.issued | 2015 | en_US |
| dc.degree.discipline | Computer Science | en_US |
| dc.degree.level | Master of Science (M.Sc.) | en_US |
| dc.description.abstract | Prior work on command recommendations for feature-rich software has relied on data supplied by a large community of users to generate personalized recommendations. In this work, I explored the feasibility of using an alternative data source: web documentation. Specifically, the proposed approach uses QF-Graphs, a previously introduced technique that maps higher-level tasks (i.e., search queries) to commands referenced in online documentation. The proposed approach uses these command-to-task mappings as an automatically generated plan library, enabling our prototype system to make personalized recommendations for task-relevant commands. Through both offline and online evaluations, I explored potential benefits and drawbacks of this approach. | en_US |
| dc.description.note | October 2015 | en_US |
| dc.identifier.citation | 0 | en_US |
| dc.identifier.uri | http://hdl.handle.net/1993/30570 | |
| dc.language.iso | eng | en_US |
| dc.publisher | ACM | en_US |
| dc.rights | open access | en_US |
| dc.subject | Feature-rich software | en_US |
| dc.subject | Software learnability | en_US |
| dc.title | QFRecs - Recommending Features in Feature-Rich Software based on Web Documentation | en_US |
| dc.type | master thesis | en_US |