A Situational Resource Rating System

A Situational Resource Rating System
Thollot, R.  Aufaure, M.-A.  
SAP BusinessObjects, Ecole Centrale Paris, Paris, France 
This paper appears in: Advances in Databases Knowledge and Data Applications (DBKDA), 2010 Second International Conference on 
Issue Date: 11-16 April 2010 
On page(s): 229 - 234 
Location: Menuires 
Print ISBN: 978-1-4244-6081-6 
INSPEC Accession Number: 11360621 
Digital Object Identifier: 10.1109/DBKDA.2010.31 
Date of Current Version: 03 June 2010

Recommendation technologies are considered a major technological trend in both industrial and academic environments. This growing interest was highlighted by, e.g., the Netflix prize which generated an intense competition. Recommender systems are crucial to support users and help them by suggesting resources relevant at a given instant. On the other hand, these systems are a core piece of e-commerce web sites, since they aim at generating more sales by encouraging users to buy more items. However, recommender systems are often designed to work with very specific types of resources, and they hardly take into account the current user's situation. In this paper, we present our approach to augment an existing recommender system with a situation model. On top of this model, we define a situational interest measure to estimate a user's interest for a resource, which we demonstrate with a prototypical implementation.
`Based on time series similarity matching algorithm for earthquake prediction research
This paper appears in: Advanced Computer Theory and Engineering (ICACTE), 2010 3rd International Conference on 
Issue Date: 20-22 Aug. 2010 
On page(s): V4-57 - V4-60 
Location: Chengdu 
ISSN: 2154-7491 
Print ISBN: 978-1-4244-6539-2 
INSPEC Accession Number: 11537354 
Digital Object Identifier: 10.1109/ICACTE.2010.5579640  
Date of Current Version: 20 September 2010 
On the basis of analyzing the newly time sequence research achievement nowadays, several...