eprintid: 733
rev_number: 8
eprint_status: archive
userid: 17
dir: disk0/00/00/07/33
datestamp: 2018-07-22 15:40:12
lastmod: 2018-07-22 15:40:12
status_changed: 2018-07-22 15:40:12
type: report
metadata_visibility: show
creators_name: Al Harbi, Fatima
creators_name: Ales, Zacharie
creators_name: Dimassi, Sabah
creators_name: Duvillié, Guillerme
creators_name: Labatut, Vincent
creators_name: Lacaux, Celine
creators_name: Linhares, Elvys
creators_name: Nguyen, Sang Thi
creators_name: Nicolau, Florentina
title: Cloud is Mine
ispublished: pub
subjects: data
studygroups: esgi117
companyname: Cloud is Mine
full_text_status: public
abstract: In this section, we introduce the company and the proposed problems. We then describe the provided database and identify some of its limitations which, to our opinion, prevent any effective resolution of the problem (Section 2). We nevertheless propose a purely theoretical solution (Section 3), but do not put it in practice because of the incomplete data. Finally, we explain how our method could be extended and improved (Section 4).
problem_statement: Cloud is Mine identified two problems related to these targeted recommendation features.
Software recommendation. The first problem is the recommendation of relevant SaaSs to a given user. This recommendation would take the form of a list of SaaSs (possibly an ordered one). Basically, two situations can occur.
1. First, if the user is anonymous, only its request can be considered: the recommendation should therefore be based on the SaaS selected by previous users with similar requests. So, to solve this problem, it is necessary to be able to compare users through their requests.
Second, if the user is identified, then we can have access to his profile, in- cluding his request history. The system should take advantage of this additional information to enhance user comparison, and therefore improve its recommen- dations.
2. Feature recommendation. The second problem is the recommendation of features to software companies. Indeed, the firms developing SaaSs want to identify the features typically desired by certain types of users, in order to include them in their products and thus increase the demand.
Again, the identification of types of users requires to be able to compare users. They can then be grouped, for example through cluster analysis.
date: 2016
date_type: published
citation:   Al Harbi, Fatima and Ales, Zacharie and Dimassi, Sabah and Duvillié, Guillerme and Labatut, Vincent and Lacaux, Celine and Linhares, Elvys and Nguyen, Sang Thi and Nicolau, Florentina  (2016) Cloud is Mine.  [Study Group Report]     
document_url: http://miis.maths.ox.ac.uk/miis/733/1/CloudIsMine.pdf