The amount of information offered by different software systems is growing exponentially and the need of personalized approaches for information access increases. This personalization aims to offer the user the pertinent information corresponding to his needs basing on his profile. For the same purpose, mediation systems have to identify user preferences in order to offer him the most relevant information .In this work we discuss different representations of user profile models designed for providing personalized information access in order to make a comparison and identify the most appropriate for our context in mediation systems.

Estimation by analogy is a commonly used software effort estimation technique and a suitable alternative to other conventional estimation techniques: It predicts the effort of the target project using information from former similar projects. While it is relatively easy to handle numerical attributes, dealing with categorical attributes is one of the most difficult issues for analogy-based estimation techniques. Therefore, we propose, in this paper, a novel analogy-based approach, called 2FA-kprototypes, to predict effort when software projects are described by a mix of numerical and categorical attributes. To this aim, the well-known fuzzy k-prototypes algorithm is integrated into the process of estimation by analogy. The estimation accuracy of 2FA-kprototypes was evaluated and compared with that of two techniques: (1) classical analogy-based technique and (2) 2FA-kmodes, which is a technique that we have developed recently. The comparison was performed using four data sets that are quite diverse and have different sizes: ISBSG, COCOMO, USP05-FT, and USP05-RQ. The results obtained showed that both 2FA-kprototypes and 2FA-kmodes perform better than classical analogy.

The aim of this paper is to evaluate and to compare the Classical Analogy and Fuzzy Analogy for software cost estimation on a Web software dataset. Hence, the paper aims to replicate the results of our precedent experiments on this dataset. Moreover, questions regarding the estimates accuracy, the tolerance of imprecision and uncertainty of cost drivers, and the favorable context to use estimation by analogy are discussed. This study approved the usefulness of Fuzzy Analogy for software cost estimation.