%0 Conference Paper %1 Ernst:2017:BSB:3077136.3084150 %A Ernst, Patrick %A Mishra, Arunav %A Anand, Avishek %A Setty, Vinay %B Proceedings of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval %C New York, NY, USA %D 2017 %I ACM %K alexandria %P 1277--1280 %R 10.1145/3077136.3084150 %T BioNex: A System For Biomedical News Event Exploration %U http://doi.acm.org/10.1145/3077136.3084150 %X We demonstrate BioNex, a system to mine, rank and visualize biomedical news events. BioNex takes biomedical queries such as "Ebola virus disease" and retrieves the k most relevant news events for them. To achieve this we first mine the generic news events by clustering them on a daily basis using general named entities and textual features. These clusters are also tagged with disambiguated biomedical entities which aid in biomedical news event exploration. The clusters are then used to compute the importance scores for the event clusters based on a combination of textual, semantic, popularity and historical importance features. BioNex also visualizes the retrieved event clusters to highlight the top news events and corresponding news articles for the given query. The visualization also provides the context for news events using (1) a chain of historically relevant news event clusters, and (2) other non-biomedical events from the same day. %@ 978-1-4503-5022-8

@inproceedings{Ernst:2017:BSB:3077136.3084150, abstract = {We demonstrate BioNex, a system to mine, rank and visualize biomedical news events. BioNex takes biomedical queries such as "Ebola virus disease" and retrieves the k most relevant news events for them. To achieve this we first mine the generic news events by clustering them on a daily basis using general named entities and textual features. These clusters are also tagged with disambiguated biomedical entities which aid in biomedical news event exploration. The clusters are then used to compute the importance scores for the event clusters based on a combination of textual, semantic, popularity and historical importance features. BioNex also visualizes the retrieved event clusters to highlight the top news events and corresponding news articles for the given query. The visualization also provides the context for news events using (1) a chain of historically relevant news event clusters, and (2) other non-biomedical events from the same day.}, acmid = {3084150}, added-at = {2018-01-24T13:21:13.000+0100}, address = {New York, NY, USA}, author = {Ernst, Patrick and Mishra, Arunav and Anand, Avishek and Setty, Vinay}, biburl = {https://www.bibsonomy.org/bibtex/2e2e18ab68cb53935f0d9e259130af175/alexandriaproj}, booktitle = {Proceedings of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval}, description = {BioNex}, doi = {10.1145/3077136.3084150}, interhash = {ba1b9e616dddfcf591cdfcf228ce322a}, intrahash = {e2e18ab68cb53935f0d9e259130af175}, isbn = {978-1-4503-5022-8}, keywords = {alexandria}, location = {Shinjuku, Tokyo, Japan}, numpages = {4}, pages = {1277--1280}, publisher = {ACM}, series = {SIGIR '17}, timestamp = {2018-01-24T13:21:13.000+0100}, title = {BioNex: A System For Biomedical News Event Exploration}, url = {http://doi.acm.org/10.1145/3077136.3084150}, year = 2017 }