Adaptation-Guided Retrieval: Using Adaptation Knowledge to Guide the Retrieval of Adaptable Cases
Oh la la
Your session has expired but don’t worry, your message
has been saved.Please log in and we’ll bring you back
to this page. You’ll just need to click “Send”.
Your evaluation is of great value to our authors and readers. Many thanks for your time.
When you're done, click "publish"
Only blue fields are mandatory.
Your mailing list is currently empty.
It will build up as you send messages
and links to your peers.
besides you has access to this list.
Enter the e-mail addresses of your recipients in the box below. Note: Peer Evaluation will NOT store these email addresses log in
Your message has been sent.
Full text for this article was not available? Send a request to the author(s)
: Adaptation-Guided Retrieval: Using Adaptation Knowledge to Guide the Retrieval of Adaptable Cases
Abstract : . Adaptation-guided retrieval is a case retrieval technique that uses "adaptability" as its core selection criterion. This means that cases are chosen for reuse according to how readily they can be adapted to fit the target problem requirements. This makes a change from traditional retrieval methods, which have concentrated on estimating adaptability in terms of semantic similarity. Unfortunately semantic similarity often fails to predict true adaptability, resulting in, at best, suboptimal retrievals, and possibly even problem solving failure. Adaptation-guided retrieval tries to remedy matters by offering a more principled and robust retrieval model. This paper explains the adaptation-guided retrieval technique in terms of its use in Dj Vu, a case-based software design system. It is shown, through a series of experiments, that adaptation-guided retrieval is more accurate than standard retrieval techniques, that it scales well to large case-bases, and that it results in mor...
: Computer Science
Leave a comment
This contribution has not been reviewed yet. review?