使用基于知识的推荐扩展wiki页面的优势

Proceedings of the 15th International Conference on Knowledge Technologies and Data-driven Business Pub Date : 2015-10-21 DOI:10.1145/2809563.2809611

Stefan Reiterer, Martin Stettinger, Michael Jeran, Wolfgang Eixelsberger, Manfred Wundara

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引用次数: 0

摘要

在本文中，我们提出了一个嵌入在Wiki环境中的基于知识的推荐系统WeeVis。由于wiki在许多公司中用于知识管理和检索已有相当长的时间，因此我们将展示如何使用知识库扩展MediaWiki页面，以便为项目提供推荐。WeeVis扩展通过向页面内容添加推荐功能，减少了从Wiki页面发现相关信息的时间。本文展示了WeeVis的两个实际应用示例(一个来自电子政务领域，另一个来自营养领域)，并概述了该系统的优点。

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Advantages of extending wiki pages with knowledge-based recommendations

In this paper we present WeeVis, a knowledge-based recommender system embedded in a Wiki environment. Since Wikis are used since quite a long time for knowledge management and retrieval in many companies, we show how MediaWiki pages can be extended with knowledge bases for deriving recommendations for items. The WeeVis extension reduces the time to discover relevant information from Wiki pages by adding recommender functionality to the page content. Two examples (one from the e-government domain and one from the nutrition domain) of real world applications of WeeVis are shown and outline the advantages of the system.

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Proceedings of the 15th International Conference on Knowledge Technologies and Data-driven Business

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