Term-weighting approaches in automatic text retrieval
Information Processing and Management: an International Journal
Recommender systems in e-commerce
Proceedings of the 1st ACM conference on Electronic commerce
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
GATE: an architecture for development of robust HLT applications
ACL '02 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics
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
Measuring semantic similarity between words using web search engines
Proceedings of the 16th international conference on World Wide Web
The Google Similarity Distance
IEEE Transactions on Knowledge and Data 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
News personalization using the CF-IDF semantic recommender
Proceedings of the International Conference on Web Intelligence, Mining and Semantics
Similarity of objects and the meaning of words
TAMC'06 Proceedings of the Third international conference on Theory and Applications of Models of Computation
Semantic web recommender systems
EDBT'04 Proceedings of the 2004 international conference on Current Trends in Database Technology
Semantics-based news recommendation
Proceedings of the 2nd International Conference on Web Intelligence, Mining and Semantics
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While traditionally content-based news recommendation was performed using the word vector space model, more recent approaches also take into account semantics, often through the use of semantic lexicons. However, named entities are rarely taken into account, as they are often absent in such lexicons. Nevertheless, they can play a crucial role in determining user interest for specific news articles. Therefore, in this work, we extend the state-of-the-art semantic lexicon-driven Semantic Similarity (SS) recommendation method by additionally considering named entities. First, as in SS, we calculate similarities between WordNet synonym sets in unread news items and synonym sets in read news items (stored in user profiles). Then, we use the page counts of named entities that are retrieved from the Bing Web search engine to compute named entity similarities between unread and read news items. Results show that our recommendation method, BingSS, outperforms SS in terms of F1, precision, accuracy, and specificity.