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BMR: Benchmarking Metrics Recommender for Personnel issues in Software Development Projects
Author(s) -
Ángel García-Crespo,
Ricardo ColomoPalacios,
Juan Miguel Gómez-Berbís,
Myriam Mencke
Publication year - 2009
Publication title -
international journal of computational intelligence systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.385
H-Index - 41
eISSN - 1875-6891
pISSN - 1875-6883
DOI - 10.1080/18756891.2009.9727658
Subject(s) - computer science , comparability , benchmarking , documentation , similarity (geometry) , set (abstract data type) , process (computing) , cluster analysis , service (business) , software , information retrieval , data science , artificial intelligence , business , mathematics , marketing , combinatorics , image (mathematics) , programming language , operating system
This paper presents an architecture which applies document similarity measures to the documentation produced during the phases of software development in order to generate recommendations of process and people metrics for similar projects. The application makes a judgment of similarity of the Service Provision Offer (SPO) document of a new proposed project to a collection of Project History Documents (PHD), stored in a repository of unstructured texts. The process is carried out in three stages: firstly, clustering of the Offer document with the set of PHDs which are most similar to it; this provides the initial indication of whether similar previous projects exist, and signifies similarity. Secondly, determination of which PHD in the set is most comparable with the Offer document, based on various parameters: project effort, project duration (time), project resources (members/size of team), costs, and sector(s) involved, indicating comparability of projects. The comparable parameters are extracted using ...

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