C4.5: programs for machine learning
C4.5: programs for machine learning
Introduction to Modern Information Retrieval
Introduction to Modern Information Retrieval
Learning Decision Trees Using the Area Under the ROC Curve
ICML '02 Proceedings of the Nineteenth International Conference on Machine Learning
A Probabilistic Analysis of the Rocchio Algorithm with TFIDF for Text Categorization
ICML '97 Proceedings of the Fourteenth International Conference on Machine Learning
Automated Collaborative Filtering Applications for Online Recruitment Services
AH '00 Proceedings of the International Conference on Adaptive Hypermedia and Adaptive Web-Based Systems
An introduction to ROC analysis
Pattern Recognition Letters - Special issue: ROC analysis in pattern recognition
Working Set Selection Using Second Order Information for Training Support Vector Machines
The Journal of Machine Learning Research
Efficient query expansion with auxiliary data structures
Information Systems
Automatic Profiling System for Ranking Candidates Answers in Human Resources
OTM '08 Proceedings of the OTM Confederated International Workshops and Posters on On the Move to Meaningful Internet Systems: 2008 Workshops: ADI, AWeSoMe, COMBEK, EI2N, IWSSA, MONET, OnToContent + QSI, ORM, PerSys, RDDS, SEMELS, and SWWS
NEO-CORTEX: A Performant User-Oriented Multi-Document Summarization System
CICLing '07 Proceedings of the 8th International Conference on Computational Linguistics and Intelligent Text Processing
E-Gen: automatic job offer processing system for human resources
MICAI'07 Proceedings of the artificial intelligence 6th Mexican international conference on Advances in artificial intelligence
Linguistic information extraction for job ads (SIRE project)
RIAO '10 Adaptivity, Personalization and Fusion of Heterogeneous Information
Pruning terminology extracted from a specialized corpus for CV ontology acquisition
OTM'06 Proceedings of the 2006 international conference on On the Move to Meaningful Internet Systems: AWeSOMe, CAMS, COMINF, IS, KSinBIT, MIOS-CIAO, MONET - Volume Part II
Error bounds for convolutional codes and an asymptotically optimum decoding algorithm
IEEE Transactions on Information Theory
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The evolution of the job market has resulted in traditional methods of recruitment becoming insufficient. As it is now necessary to handle volumes of information (mostly in the form of free text) that are impossible to process manually, an analysis and assisted categorization are essential to address this issue. In this paper, we present a combination of the E-Gen and Cortex systems. E-Gen aims to perform analysis and categorization of job offers together with the responses given by the candidates. E-Gen system strategy is based on vectorial and probabilistic models to solve the problem of profiling applications according to a specific job offer. Cortex is a statistical automatic summarization system. In this work, E-Gen uses Cortex as a powerful filter to eliminate irrelevant information contained in candidate answers. Our main objective is to develop a system to assist a recruitment consultant and the results obtained by the proposed combination surpass those of E-Gen in standalone mode on this task.