Introduction to Modern Information Retrieval
Introduction to Modern Information Retrieval
An Information-Theoretic Definition of Similarity
ICML '98 Proceedings of the Fifteenth International Conference on Machine Learning
Comparing Hierarchical Data in External Memory
VLDB '99 Proceedings of the 25th International Conference on Very Large Data Bases
Verbs semantics and lexical selection
ACL '94 Proceedings of the 32nd annual meeting on Association for Computational Linguistics
Fast Detection of XML Structural Similarity
IEEE Transactions on Knowledge and Data Engineering
A survey on tree edit distance and related problems
Theoretical Computer Science
Evaluating WordNet-based Measures of Lexical Semantic Relatedness
Computational Linguistics
ICTAI '06 Proceedings of the 18th IEEE International Conference on Tools with Artificial Intelligence
Matching XML documents in highly dynamic applications
Proceedings of the eighth ACM symposium on Document engineering
A Hybrid Approach for XML Similarity
SOFSEM '07 Proceedings of the 33rd conference on Current Trends in Theory and Practice of Computer Science
A unifying framework for merging and evaluating XML information
DASFAA'05 Proceedings of the 10th international conference on Database Systems for Advanced Applications
Implicit news recommendation based on user interest models and multimodal content analysis
Proceedings of the 3rd international workshop on Automated information extraction in media production
Semantics-based news recommendation
Proceedings of the 2nd International Conference on Web Intelligence, Mining and Semantics
visualRSS: a platform to mine and visualise social data from RSS feeds
ICWE'12 Proceedings of the 12th international conference on Current Trends in Web Engineering
Multimedia Tools and Applications
A Comparison Study for Novelty Control Mechanisms Applied to Web News Stories
WI-IAT '12 Proceedings of the The 2012 IEEE/WIC/ACM International Joint Conferences on Web Intelligence and Intelligent Agent Technology - Volume 01
Semantics-based news recommendation with SF-IDF+
Proceedings of the 3rd International Conference on Web Intelligence, Mining and Semantics
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Merging related RSS news (coming from one or different sources) is beneficial for end-users with different backgrounds (journalists, economists, etc.), particularly those accessing similar information. In this paper, we provide a practical approach to both: measure the relatedness, and identify relationships between RSS elements. Our approach is based on the concepts of semantic neighborhood and vector space model, and considers the content and structure of RSS news items.