COMPANION PROCEEDINGS OF THE WEB CONFERENCE 2022, WWW 2022 COMPANION(2022)
Univ Caen Normandie
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摘要
TempWeb focuses on investigating infrastructures, scalable methods, and innovative software for aggregating, querying, and analyzing heterogeneous data at Web scale. Emphasis is given to data analysis along the time dimension for web data that has been collected over extended time periods. A major challenge in this regard is the sheer size of the data it exposes and the ability to make sense of it in a useful and meaningful manner for its users. It is worth noting that this trend of using big data to make inferences is not specific to Web content analytics, so work presented here might be useful in other areas, too. As such, longitudinal aspects in Web content analysis become relevant for analysts from from various domains, including, but not limited to sociology, marketing, environmental studies, politics, etc. Studies in this context range from "low-level" structural network log analysis over time, up to "high-level" entity-levelWeb content analytics and terminology evolution. While both before mentioned aspects represent the extremes of the spectrum, they have one thing in common: Web scale data analytics needs to develop infrastructures and extended analytical tools in order to make use of that data. TempWeb has been created for this purpose and is the ideal venue to discuss about all its facets.
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关键词
Temporal Web Analytics,Web Scale Data Analytics,Web Science,Web Dynamics,Web Trends,Data Mining