%0 Journal Article %1 1083153 %A Hayes, Jane Huffman %A Dekhtyar, Alex %A Sundaram, Senthil %C New York, NY, USA %D 2005 %I ACM %J SIGSOFT Softw. Eng. Notes %K engineering mining software text %N 4 %P 1--5 %R http://doi.acm.org/10.1145/1082983.1083153 %T Text mining for software engineering: how analyst feedback impacts final results %U http://portal.acm.org/citation.cfm?id=1082983.1083153 %V 30 %X The mining of textual artifacts is requisite for many important activities in software engineering: tracing of requirements; retrieval of components from a repository; location of manpage text for an area of question, etc. Many such activities leave the "final word" to the analyst --- have the relevant items been retrieved? are there other items that should have been retrieved? When analysts become a part of the text mining process, their decisions on the relevance of retrieved elements impact the final outcome of the activity. In this paper, we undertook a pilot study to examine the impact of analyst decisions on the final outcome of a task.

@article{1083153, abstract = {The mining of textual artifacts is requisite for many important activities in software engineering: tracing of requirements; retrieval of components from a repository; location of manpage text for an area of question, etc. Many such activities leave the "final word" to the analyst --- have the relevant items been retrieved? are there other items that should have been retrieved? When analysts become a part of the text mining process, their decisions on the relevance of retrieved elements impact the final outcome of the activity. In this paper, we undertook a pilot study to examine the impact of analyst decisions on the final outcome of a task.}, added-at = {2008-03-07T15:06:58.000+0100}, address = {New York, NY, USA}, author = {Hayes, Jane Huffman and Dekhtyar, Alex and Sundaram, Senthil}, biburl = {https://www.bibsonomy.org/bibtex/2dcbda00e6fadfafd0495274e1eeed893/renew}, description = {Text mining for software engineering}, doi = {http://doi.acm.org/10.1145/1082983.1083153}, interhash = {c26ebd98e601fd6cec58b5fa4b8540d8}, intrahash = {dcbda00e6fadfafd0495274e1eeed893}, issn = {0163-5948}, journal = {SIGSOFT Softw. Eng. Notes}, keywords = {engineering mining software text}, number = 4, pages = {1--5}, publisher = {ACM}, timestamp = {2008-03-07T15:06:58.000+0100}, title = {Text mining for software engineering: how analyst feedback impacts final results}, url = {http://portal.acm.org/citation.cfm?id=1082983.1083153}, volume = 30, year = 2005 }