Fuzzy Linguistic Summaries in Rule-Based Adaptive Hypermedia Systems
نویسندگان
چکیده
Rule-based adaptive hypermedia systems personalize the structure of the hypermedia space using an inference mechanism that operates on a specific knowledge representation about its users. Approximate quantifiers are very frequently used in human language expressions that entail the summarization of a large number of facts. We describe how quantified expressions can be used in adaptation rules to specify common adaptation behaviors, enhancing rule’s expressive power for the human expert. Those quantified expressions can be implemented through fuzzy quantification mechanisms operating on fuzzy linguistic labels and relations, and can be integrated as extensions in generalpurpose rule-based adaptive hypermedia systems.
منابع مشابه
Berkovsky, Shlomo, Timothy Baldwin and Ingrid Zukerman (2008) Aspect-Based Personalized Text Summarization, In Proceedings of the 5th International Conference on Adaptive Hypermedia and Adaptive Web-Based Systems, Hanover, Germany, pp. 267-270
This work investigates user attitudes towards personalized summaries generated from a coarse-grained user model based on document aspects. We explore user preferences for summaries at differing degrees of fit with their stated interests, the impact of length on user ratings, and the faithfulness of personalized and general summaries.
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