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- W4285220802 abstract "The World Wide Web is the most extensive knowledge repository and the vastest record structure that has ever existed in human history. A socially aware and semantically driven web page recommendation algorithm is therefore a compelling necessity. In this paper, an entity enrichment mechanism for recommendation of web pages has been proposed. The approach incorporates semantic frame matching and entities enriched by generation of Resource Description Framework along with the incorporation of background knowledge from the Linked Open Data cloud, social awareness is incorporated by including entities from the Twitter API. The dataset is classified using the XGBoosting algorithm, and the SemantoSim measure has been chosen to compute the semantic similarity under LION optimization algorithm which serves as the metaheuristics. The approach considers the user query, the current user clicks as well as web usage data of the user. The proposed methodology yields an accuracy of 95.42% which surpasses the existing techniques." @default.
- W4285220802 created "2022-07-14" @default.
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- W4285220802 date "2022-01-01" @default.
- W4285220802 modified "2023-09-28" @default.
- W4285220802 title "IEESWPR: An Integrative Entity Enrichment Scheme for Socially Aware Web Page Recommendation" @default.
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- W4285220802 doi "https://doi.org/10.1007/978-981-19-2211-4_21" @default.
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