Term-weighting approaches in automatic text retrieval
Information Processing and Management: an International Journal
An Information-Theoretic Definition of Similarity
ICML '98 Proceedings of the Fifteenth International Conference on Machine Learning
An Adapted Lesk Algorithm for Word Sense Disambiguation Using WordNet
CICLing '02 Proceedings of the Third International Conference on Computational Linguistics and Intelligent Text Processing
Verbs semantics and lexical selection
ACL '94 Proceedings of the 32nd annual meeting on Association for Computational Linguistics
IEEE Transactions on Knowledge and Data Engineering
Feature-rich part-of-speech tagging with a cyclic dependency network
NAACL '03 Proceedings of the 2003 Conference of the North American Chapter of the Association for Computational Linguistics on Human Language Technology - Volume 1
Open user profiles for adaptive news systems: help or harm?
Proceedings of the 16th international conference on World Wide Web
Hermes: a semantic web-based news decision support system
Proceedings of the 2008 ACM symposium on Applied computing
ICWE '9 Proceedings of the 9th International Conference on Web Engineering
WordNet: similarity - measuring the relatedness of concepts
AAAI'04 Proceedings of the 19th national conference on Artifical intelligence
Using information content to evaluate semantic similarity in a taxonomy
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 1
Ontology-based news recommendation
Proceedings of the 2010 EDBT/ICDT Workshops
Modern Information Retrieval
News personalization using the CF-IDF semantic recommender
Proceedings of the International Conference on Web Intelligence, Mining and Semantics
Semantics-based news recommendation with SF-IDF+
Proceedings of the 3rd International Conference on Web Intelligence, Mining and Semantics
Semantic news recommendation using wordnet and bing similarities
Proceedings of the 28th Annual ACM Symposium on Applied Computing
Modeling and broadening temporal user interest in personalized news recommendation
Expert Systems with Applications: An International Journal
Hi-index | 0.00 |
News item recommendation is commonly performed using the TF-IDF weighting technique in combination with the cosine similarity measure. However, this technique does not take into account the actual meaning of words. Therefore, we propose two new methods based on concepts and their semantic similarities, from which we derive the similarities between news items. Our first method, Synset Frequency -- Inverse Document Frequency (SF-IDF), is similar to TF-IDF, yet it does not use terms, but WordNet synonym sets. Additionally, our second method, Semantic Similarity (SS), makes use of five semantic similarity measures to compute the similarity between news items for news recommendation. Test results show that SF-IDF and SS outperform the TF-IDF method on the F1-measure.