Improving new user recommendations with rule-based induction on cold user data

2007 ◽  
Author(s):  
An-Te Nguyen ◽  
Nathalie Denos ◽  
Catherine Berrut
Keyword(s):  
Rule Based ◽  
User Data

An Efficient E-Negotiation Agent Using Rule-Based and Case-Based Approaches

2015 ◽  
pp. 245-261
Author(s):  
Amruta More ◽  
Sheetal Vij ◽  
Debajyoti Mukhopadhyay
Keyword(s):  
Product Information ◽  
Negotiation Process ◽  
Case Based Reasoning ◽  
Bilateral Negotiation ◽  
User Requirement ◽  
Rule Based ◽  
Negotiation Model ◽  
User Data ◽  
Training And Research ◽  
Case Based

The research in the area of automated negotiation systems is going on in many universities. This research is mainly focused on making a practically feasible, faster and reliable E-negotiation system. The ongoing work in this area is happening in the laboratories of the universities mainly for training and research purpose. There are number of negotiation systems such as Henry, Kasbaah, Bazaar, Auction Bot, Inspire, Magnet. Our research is based on making an agent software for E-negotiation which will give faster results and also is secure and flexible. Cloud Computing provides security and flexibility to the user data. Using these features we propose an E-negotiation system, in which, all product information and agent details are stored on the cloud. This system proposes three conditions for making successful negotiation. First rule based, where agent will check user requirements with rule based data. Second case based, where an agent will see case based data to check any similar previous negotiation case is matching to the user requirement. Third bilateral negotiation model, if both rules based data and case based data are not matching with the user requirement, then agent use bilateral negotiation model for negotiation. After completing negotiation process, agents give feedback to the user about whether negotiation is successful or not. Using rule based reasoning and case based reasoning this system will improve the efficiency and success rate of the negotiation process.

Meta-Rule Based Recommender Systems for Educational Applications

2012 ◽  
pp. 211-231 ◽  
Author(s):  
Vicente Arturo Romero Zaldivar ◽  
Daniel Burgos ◽  
Abelardo Pardo
Keyword(s):  
Recommendation System ◽  
Recommendation Systems ◽  
Relevant Information ◽  
User Preferences ◽  
Personalized Recommendation ◽  
Rule Based ◽  
User Data ◽  
Rule Sets ◽  
Rule Set ◽  
Educational Applications

Recommendation Systems are central in current applications to help the user find relevant information spread in large amounts of data. Most Recommendation Systems are more effective when huge amounts of user data are available. Educational applications are not popular enough to generate large amount of data. In this context, rule-based Recommendation Systems seem a better solution. Rules can offer specific recommendations with even no usage information. However, large rule-sets are hard to maintain, reengineer, and adapt to user preferences. Meta-rules can generalize a rule-set which provides bases for adaptation. In this chapter, the authors present the benefits of meta-rules, implemented as part of Meta-Mender, a meta-rule based Recommendation System. This is an effective solution to provide a personalized recommendation to the learner, and constitutes a new approach to Recommendation Systems.

An Efficient E-Negotiation Agent Using Rule-Based and Case-Based Approaches

2016 ◽  
pp. 1003-1016
Author(s):  
Amruta More ◽  
Sheetal Vij ◽  
Debajyoti Mukhopadhyay
Keyword(s):  
Product Information ◽  
Negotiation Process ◽  
Case Based Reasoning ◽  
Bilateral Negotiation ◽  
User Requirement ◽  
Rule Based ◽  
Negotiation Model ◽  
User Data ◽  
Training And Research ◽  
Case Based

The research in the area of automated negotiation systems is going on in many universities. This research is mainly focused on making a practically feasible, faster and reliable E-negotiation system. The ongoing work in this area is happening in the laboratories of the universities mainly for training and research purpose. There are number of negotiation systems such as Henry, Kasbaah, Bazaar, Auction Bot, Inspire, Magnet. Our research is based on making an agent software for E-negotiation which will give faster results and also is secure and flexible. Cloud Computing provides security and flexibility to the user data. Using these features we propose an E-negotiation system, in which, all product information and agent details are stored on the cloud. This system proposes three conditions for making successful negotiation. First rule based, where agent will check user requirements with rule based data. Second case based, where an agent will see case based data to check any similar previous negotiation case is matching to the user requirement. Third bilateral negotiation model, if both rules based data and case based data are not matching with the user requirement, then agent use bilateral negotiation model for negotiation. After completing negotiation process, agents give feedback to the user about whether negotiation is successful or not. Using rule based reasoning and case based reasoning this system will improve the efficiency and success rate of the negotiation process.

scholarly journals A Flexible Rule-Based Method for Interlinking, Integrating, and Enriching User Data

2010 ◽  
pp. 322-336 ◽  
Author(s):  
Erwin Leonardi ◽  
Fabian Abel ◽  
Dominikus Heckmann ◽  
Eelco Herder ◽  
Jan Hidders ◽  
...  
Keyword(s):  
Rule Based ◽  
User Data

Using Conventional Articulation Tests With Highly Unintelligible Children

1992 ◽  
Vol 23 (1) ◽  
pp. 52-60 ◽  
Author(s):  
Pamela G. Garn-Nunn ◽  
Vicki Martin
Keyword(s):  
Test Results ◽  
Phonological Processes ◽  
Rule Based ◽  
Severity Level ◽  
Error Sensitivity ◽  
Conventional Tests ◽  
Severity Levels ◽  
Conventional Test ◽  
Impaired Children

This study explored whether or not standard administration and scoring of conventional articulation tests accurately identified children as phonologically disordered and whether or not information from these tests established severity level and programming needs. Results of standard scoring procedures from the Assessment of Phonological Processes-Revised, the Goldman-Fristoe Test of Articulation, the Photo Articulation Test, and the Weiss Comprehensive Articulation Test were compared for 20 phonologically impaired children. All tests identified the children as phonologically delayed/disordered, but the conventional tests failed to clearly and consistently differentiate varying severity levels. Conventional test results also showed limitations in error sensitivity, ease of computation for scoring procedures, and implications for remediation programming. The use of some type of rule-based analysis for phonologically impaired children is highly recommended.

Haunted by a Doppelgänger

2014 ◽  
Vol 61 (1) ◽  
pp. 12-22 ◽  
Author(s):  
Bettina von Helversen ◽  
Stefan M. Herzog ◽  
Jörg Rieskamp
Keyword(s):  
Relevant Information ◽  
Psychological Research ◽  
Decision Makers ◽  
Human Judgment ◽  
Rule Based ◽  
New Employees ◽  
High Performing ◽  
Facial Similarity ◽  
Similarity Effect ◽  
Judgment Strategy

Judging other people is a common and important task. Every day professionals make decisions that affect the lives of other people when they diagnose medical conditions, grant parole, or hire new employees. To prevent discrimination, professional standards require that decision makers render accurate and unbiased judgments solely based on relevant information. Facial similarity to previously encountered persons can be a potential source of bias. Psychological research suggests that people only rely on similarity-based judgment strategies if the provided information does not allow them to make accurate rule-based judgments. Our study shows, however, that facial similarity to previously encountered persons influences judgment even in situations in which relevant information is available for making accurate rule-based judgments and where similarity is irrelevant for the task and relying on similarity is detrimental. In two experiments in an employment context we show that applicants who looked similar to high-performing former employees were judged as more suitable than applicants who looked similar to low-performing former employees. This similarity effect was found despite the fact that the participants used the relevant résumé information about the applicants by following a rule-based judgment strategy. These findings suggest that similarity-based and rule-based processes simultaneously underlie human judgment.

A Neurocomputational Model of Criterion Learning in Rule-Based Categorization

2012 ◽  
Author(s):  
Sebastien Helie ◽  
Shawn W. Ell ◽  
J. Vincent Filoteo ◽  
Brian D. Glass ◽  
W. W. Todd Maddox
Keyword(s):  
Rule Based ◽  
Criterion Learning
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