%0 Conference Paper %1 Singh:2015:ELR:2786451.2786489 %A Singh, Jaspreet %A Anand, Abhijit %A Setty, Vinay %A Anand, Avishek %B Proceedings of the ACM Web Science Conference %C New York, NY, USA %D 2015 %I ACM %K alexandria %P 57:1--57:2 %R 10.1145/2786451.2786489 %T Exploring Long Running News Stories Using Wikipedia %U http://doi.acm.org/10.1145/2786451.2786489 %X A significant portion of today's news articles are part of long running stories. To better understand the context of these stories journalists, social scientists and other scholars use news collections to find temporal and topical insights. However these insights are devoid of user impressions, derived from click-through data and query logs, and are only reliable if the collection is complete and consistent. In this work we introduce the notion of combining user impressions from Wikipedia with news collection based insights for long running news story exploration and outline promising new research directions. We also demonstrate our initial attempts with a prototype system called NewsEX. %@ 978-1-4503-3672-7

@inproceedings{Singh:2015:ELR:2786451.2786489, abstract = {A significant portion of today's news articles are part of long running stories. To better understand the context of these stories journalists, social scientists and other scholars use news collections to find temporal and topical insights. However these insights are devoid of user impressions, derived from click-through data and query logs, and are only reliable if the collection is complete and consistent. In this work we introduce the notion of combining user impressions from Wikipedia with news collection based insights for long running news story exploration and outline promising new research directions. We also demonstrate our initial attempts with a prototype system called NewsEX.}, acmid = {2786489}, added-at = {2016-08-24T10:50:11.000+0200}, address = {New York, NY, USA}, articleno = {57}, author = {Singh, Jaspreet and Anand, Abhijit and Setty, Vinay and Anand, Avishek}, biburl = {https://www.bibsonomy.org/bibtex/22ef171c183a1c31303f21fd9fc6fae22/alexandriaproj}, booktitle = {Proceedings of the ACM Web Science Conference}, doi = {10.1145/2786451.2786489}, interhash = {80d0b9d8534f844790099ac4c459239e}, intrahash = {2ef171c183a1c31303f21fd9fc6fae22}, isbn = {978-1-4503-3672-7}, keywords = {alexandria}, location = {Oxford, United Kingdom}, numpages = {2}, pages = {57:1--57:2}, publisher = {ACM}, series = {WebSci '15}, timestamp = {2016-08-24T10:50:11.000+0200}, title = {Exploring Long Running News Stories Using Wikipedia}, url = {http://doi.acm.org/10.1145/2786451.2786489}, year = 2015 }