Foundations of Inductive Logic Programming
Foundations of Inductive Logic Programming
Learning Algorithms for Keyphrase Extraction
Information Retrieval
A statistical approach to mechanized encoding and searching of literary information
IBM Journal of Research and Development
Efficient food retrieval techniques considering relative frequencies of food related words
ICHIT'11 Proceedings of the 5th international conference on Convergence and hybrid information technology
Rule-based personalized comparison shopping including delivery cost
Electronic Commerce Research and Applications
Creating a testbed for the evaluation of automatically generated back-of-the-book indexes
CICLing'06 Proceedings of the 7th international conference on Computational Linguistics and Intelligent Text Processing
Automatic keyphrases extraction from document using neural network
ICMLC'05 Proceedings of the 4th international conference on Advances in Machine Learning and Cybernetics
Detecting weak signals for long-term business opportunities using text mining of Web news
Expert Systems with Applications: An International Journal
Automatic keyword extraction from single-sentence natural language queries
PRICAI'12 Proceedings of the 12th Pacific Rim international conference on Trends in Artificial Intelligence
Keyword extraction for blogs based on content richness
Journal of Information Science
Contextual keyword extraction by building sentences with crowdsourcing
Multimedia Tools and Applications
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Documents can be assigned keywords by frequency analysis of the terms found in the document text, which arguably is the primary source of knowledge about the document itself. By including a hierarchically organised domain specific thesaurus as a second knowledge source the quality of such keywords was improved considerably, as measured by match to previously manually assigned keywords. In the presented experiment, the combination of the evidence from frequency analysis and the hierarchically organised thesaurus was done using inductive logic programming.