Inferring web citations using social data and SPARQL rules
作者： Matthew Rowe
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摘要: Web users who disseminate their personal information risk falling victims to malevolent web practices such as lateral surveillance and identity theft. To avoid practices, must manually search for resources which may cite them then perform analyses decide do them; a time-consuming frequently repeated practice. This paper presents automated rule-based technique identify citations, intended alleviate this manual process. Seed data is leveraged from user profiles on various Social platforms used seed SPARQL rules are constructed applied in infer citations. An evaluation of against humans performing the same task shows higher levels precision.
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