ABSTRACT
Content-based news recommendations are usually made by employing the cosine similarity and the TF-IDF weighting scheme for terms occurring in news messages and user profiles. Recent developments, such as SF-IDF, have elevated news recommendation to a new level of abstraction by additionally taking into account term meaning through the exploitation of synsets from semantic lexicons and the cosine similarity. Other state-of-the-art semantic recommenders, like SS, make use of semantic lexicon-driven similarities. A shortcoming of current semantic recommenders is that they do not take into account the various semantic relationships between synsets, providing only for a limited understanding of news semantics. Therefore, we extend the SF-IDF weighting technique by additionally considering the synset semantic relationships from a semantic lexicon. The proposed recommendation method, SF-IDF+, as well as SF-IDF and several semantic similarity lexicon-driven methods have been implemented in Ceryx, an extension to the Hermes news personalization service. An evaluation on a data set containing financial news messages shows that overall (by accounting for all considered cut-off values) SF-IDF+ outperforms TF-IDF, SS, and SF-IDF in terms of F1-scores.
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Index Terms
Semantics-based news recommendation with SF-IDF+
Recommendations
Semantics-based news recommendation
WIMS '12: Proceedings of the 2nd International Conference on Web Intelligence, Mining and SemanticsNews 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 ...
News personalization using the CF-IDF semantic recommender
WIMS '11: Proceedings of the International Conference on Web Intelligence, Mining and SemanticsWhen recommending news items, most of the traditional algorithms are based on TF-IDF, i.e., a term-based weighting method which is mostly used in information retrieval and text mining. However, many new technologies have been made available since the ...
Ontology-based news recommendation
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