%0 Book Section %1 noKey %A Tran, Tuan %A Ceroni, Andrea %A Georgescu, Mihai %A Djafari Naini, Kaweh %A Fisichella, Marco %B Web Information Systems Engineering – WISE 2014 %D 2014 %E Benatallah, Boualem %E Bestavros, Azer %E Manolopoulos, Yannis %E Vakali, Athena %E Zhang, Yanchun %I Springer International Publishing %K myown %P 90-108 %R 10.1007/978-3-319-11746-1_7 %T WikipEvent: Leveraging Wikipedia Edit History for Event Detection %U http://dx.doi.org/10.1007/978-3-319-11746-1_7 %V 8787 %X Much of existing work in information extraction assumes the static nature of relationships in fixed knowledge bases. However, in collaborative environments such as Wikipedia, information and structures are highly dynamic over time. In this work, we introduce a new method to extract complex event structures from Wikipedia. We propose a new model to represent events by engaging multiple entities, generalizable to an arbitrary language. The evolution of an event is captured effectively based on analyzing the user edits history in Wikipedia. Our work provides a foundation for a novel class of evolution-aware entity-based enrichment algorithms, and considerably increases the quality of entity accessibility and temporal retrieval for Wikipedia. We formalize this problem and introduce an efficient end-to-end platform as a solution. We conduct comprehensive experiments on a real dataset of %@ 978-3-319-11745-4

@incollection{noKey, abstract = {Much of existing work in information extraction assumes the static nature of relationships in fixed knowledge bases. However, in collaborative environments such as Wikipedia, information and structures are highly dynamic over time. In this work, we introduce a new method to extract complex event structures from Wikipedia. We propose a new model to represent events by engaging multiple entities, generalizable to an arbitrary language. The evolution of an event is captured effectively based on analyzing the user edits history in Wikipedia. Our work provides a foundation for a novel class of evolution-aware entity-based enrichment algorithms, and considerably increases the quality of entity accessibility and temporal retrieval for Wikipedia. We formalize this problem and introduce an efficient end-to-end platform as a solution. We conduct comprehensive experiments on a real dataset of }, added-at = {2015-01-16T10:28:20.000+0100}, author = {Tran, Tuan and Ceroni, Andrea and Georgescu, Mihai and Djafari Naini, Kaweh and Fisichella, Marco}, biburl = {https://www.bibsonomy.org/bibtex/2ec0aa2322f03d2cd3251244ac39155cb/xander71988}, booktitle = {Web Information Systems Engineering – WISE 2014}, doi = {10.1007/978-3-319-11746-1_7}, editor = {Benatallah, Boualem and Bestavros, Azer and Manolopoulos, Yannis and Vakali, Athena and Zhang, Yanchun}, interhash = {9d16b459f07c9af8375bbf2487d8b7e1}, intrahash = {ec0aa2322f03d2cd3251244ac39155cb}, isbn = {978-3-319-11745-4}, keywords = {myown}, language = {English}, pages = {90-108}, publisher = {Springer International Publishing}, series = {Lecture Notes in Computer Science}, timestamp = {2015-01-16T10:28:20.000+0100}, title = {WikipEvent: Leveraging Wikipedia Edit History for Event Detection}, url = {http://dx.doi.org/10.1007/978-3-319-11746-1_7}, volume = 8787, year = 2014 }