Automatic text processing: the transformation, analysis, and retrieval of information by computer
Automatic text processing: the transformation, analysis, and retrieval of information by computer
An evaluation of phrasal and clustered representations on a text categorization task
SIGIR '92 Proceedings of the 15th annual international ACM SIGIR conference on Research and development in information retrieval
Using WordNet to disambiguate word senses for text retrieval
SIGIR '93 Proceedings of the 16th annual international ACM SIGIR conference on Research and development in information retrieval
Word sense disambiguation for free-text indexing using a massive semantic network
CIKM '93 Proceedings of the second international conference on Information and knowledge management
SIGIR '94 Proceedings of the 17th annual international ACM SIGIR conference on Research and development in information retrieval
Query expansion using lexical-semantic relations
SIGIR '94 Proceedings of the 17th annual international ACM SIGIR conference on Research and development in information retrieval
The nature of statistical learning theory
The nature of statistical learning theory
Making large-scale support vector machine learning practical
Advances in kernel methods
An introduction to support Vector Machines: and other kernel-based learning methods
An introduction to support Vector Machines: and other kernel-based learning methods
An Evaluation of Statistical Approaches to Text Categorization
Information Retrieval
On feature distributional clustering for text categorization
Proceedings of the 24th annual international ACM SIGIR conference on Research and development in information retrieval
Natural Language Information Retrieval
Natural Language Information Retrieval
Journal of Intelligent Information Systems
Class-based probability estimation using a semantic hierarchy
Computational Linguistics
Feature Engineering for Text Classification
ICML '99 Proceedings of the Sixteenth International Conference on Machine Learning
The Role of Conceptual Relation in Word Sense Disambiguation
NLDB'01 Proceedings of the 6th International Workshop on Applications of Natural Language to Information Systems
Support Vector Machines Based on a Semantic Kernel for Text Categorization
IJCNN '00 Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks (IJCNN'00)-Volume 5 - Volume 5
Generalizing case frames using a thesaurus and the MDL principle
Computational Linguistics
Word sense disambiguation using Conceptual Density
COLING '96 Proceedings of the 16th conference on Computational linguistics - Volume 1
Combined syntactic and semantic Kernels for text classification
ECIR'07 Proceedings of the 29th European conference on IR research
Text relatedness based on a word thesaurus
Journal of Artificial Intelligence Research
A knowledge-based semantic Kernel for text classification
SPIRE'11 Proceedings of the 18th international conference on String processing and information retrieval
SemaFor: semantic document indexing using semantic forests
Proceedings of the 21st ACM international conference on Information and knowledge management
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Improving accuracy in Information Retrieval tasks via semantic information is a complex problem characterized by three main aspects: the document representation model, the similarity estimation metric and the inductive algorithm. In this paper an original kernel function sensitive to external semantic knowledge is defined as a document similarity model. This semantic kernel was tested over a text categorization task, under critical learning conditions (i.e. poor training data). The results of cross-validation experiments suggest that the proposed kernel function can be used as a general model of document similarity for IR tasks.