most citedSemantic URL Analytics to Support Efficient Annotation of Large Scale Web Archives

11 citations · 18 across the 6 of their papers we have counts for

collaborators

6 papers

cs.DL2017

Extracting Event-Centric Document Collections from Large-Scale Web Archives

Gerhard Gossen, Elena Demidova, Thomas Risse

Web archives are typically very broad in scope and extremely large in scale. This makes data analysis appear daunting, especially for non-computer scientists. These collections con…

cs.CL20171 cited

Named Entity Evolution Recognition on the Blogosphere

Helge Holzmann, Nina Tahmasebi, Thomas Risse

Advancements in technology and culture lead to changes in our language. These changes create a gap between the language known by users and the language stored in digital archives.…

cs.CL2017

Extraction of Evolution Descriptions from the Web

Helge Holzmann, Thomas Risse

The evolution of named entities affects exploration and retrieval tasks in digital libraries. An information retrieval system that is aware of name changes can actively support use…

cs.CL20176 cited

Named Entity Evolution Analysis on Wikipedia

Helge Holzmann, Thomas Risse

Accessing Web archives raises a number of issues caused by their temporal characteristics. Additional knowledge is needed to find and understand older texts. Especially entities me…

cs.CL2017

Insights into Entity Name Evolution on Wikipedia

Helge Holzmann, Thomas Risse

Working with Web archives raises a number of issues caused by their temporal characteristics. Depending on the age of the content, additional knowledge might be needed to find and…

cs.IR201711 cited

Semantic URL Analytics to Support Efficient Annotation of Large Scale Web Archives

Tarcisio Souza, Elena Demidova, Thomas Risse +3

Long-term Web archives comprise Web documents gathered over longer time periods and can easily reach hundreds of terabytes in size. Semantic annotations such as named entities can…