Learning User Preferences in Case-Based Software Reuse

2000 ◽  
pp. 112-123 ◽  
Author(s):  
Paulo Gomes ◽  
Carlos Bento
Keyword(s):  
Software Reuse ◽  
User Preferences ◽  
Case Based

Task Allocation in Case-Based Recommender Systems

2011 ◽  
pp. 268-279 ◽  
Author(s):  
Fabiana Lorenzi ◽  
Daniela Scherer dos Santos ◽  
Denise de Oliveira ◽  
Ana L.C. Bazzan
Keyword(s):  
Swarm Intelligence ◽  
Recommender Systems ◽  
Recommender System ◽  
Task Allocation ◽  
User Preferences ◽  
Cooperative Agents ◽  
Over Time ◽  
Case Based

Case-based recommender systems can learn about user preferences over time and automatically suggest products that fit these preferences. In this chapter, we present such a system, called CASIS. In CASIS, we combined the use of swarm intelligence in the task allocation among cooperative agents applied to a case-based recommender system to help the user to plan a trip.

Case-based support system to facilitate software reuse

1999 ◽  
Vol 21 (2) ◽  
pp. 172
Author(s):  
John G. Morris ◽  
Christine M. Mitchell
Keyword(s):  
Support System ◽  
Software Reuse ◽  
Case Based

A case-based approach to software reuse

1993 ◽  
Vol 2 (2) ◽  
pp. 165-197 ◽  
Author(s):  
Gilles Fouqu� ◽  
Stan Matwin
Keyword(s):  
Software Reuse ◽  
Case Based

Agents for case-based software reuse

2001 ◽  
Vol 15 (3) ◽  
pp. 297-332 ◽  
Author(s):  
Stein Inge Morisbak ◽  
Bjornar Tessem
Keyword(s):  
Software Reuse ◽  
Case Based

A case similarity metric for software reuse and design

2001 ◽  
Vol 15 (1) ◽  
pp. 21-35 ◽  
Author(s):  
PAULO GOMES ◽  
CARLOS BENTO
Keyword(s):  
Software Design ◽  
Software Reuse ◽  
Software Component ◽  
Case Based Reasoning ◽  
Similarity Metric ◽  
New Horizons ◽  
Efficient Retrieval ◽  
The Right ◽  
Case Based ◽  
Selection Of

When the idea of software reuse appeared in 1968, new horizons for software design were open. But some major problems appeared and most of the expectations were not met. One of the problems encountered is the selection of the right software component. This is related not only to the similarity between the desired functionality and the function delivered by the retrieved software component, but also to the effort needed to modify the chosen component to accommodate the desired functionality. Most of the research done in the case-based reasoning area has been in developing accurate and efficient retrieval algorithms. We think that case-based reasoning retrieval concepts and ideas can be successfully applied to software reuse. In this article we propose a metric to assess similarity between software cases supported on functional and behavioral knowledge. One important aspect of this metric is that reusability is taken into account to estimate the amount of effort needed to reuse retrieved software cases. We also present experimental work that shows that similarity at the functional level is the most important aspect of the similarity metric proposed.

Sign in / Sign up

Export Citation Format

Share Document