Details
| Originalsprache | Englisch |
|---|---|
| Titel des Sammelwerks | SIGIR 2017 - Proceedings of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval |
| Herausgeber (Verlag) | Association for Computing Machinery (ACM) |
| Seiten | 1277-1280 |
| Seitenumfang | 4 |
| ISBN (elektronisch) | 9781450350228 |
| Publikationsstatus | Veröffentlicht - 2017 |
| Veranstaltung | 40th International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2017 - Tokyo, Shinjuku, Japan Dauer: 7 Aug. 2017 → 11 Aug. 2017 |
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. These 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.
ASJC Scopus Sachgebiete
- Informatik (insg.)
- Information systems
- Informatik (insg.)
- Software
- Informatik (insg.)
- Computergrafik und computergestütztes Design
Ziele für nachhaltige Entwicklung
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SIGIR 2017 - Proceedings of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval. Association for Computing Machinery (ACM), 2017. S. 1277-1280.
Publikation: Beitrag in Buch/Bericht/Sammelwerk/Konferenzband › Aufsatz in Konferenzband › Forschung › Peer-Review
}
TY - GEN
T1 - BioNex: A System For Biomedical News Event Exploration
AU - Ernst, Patrick
AU - Mishra, Arunav
AU - Anand, Avishek
AU - Setty, Vinay
N1 - Funding information: Œis research was partially funded by the Danish Council for Independent Research under grant agreement DFF-4093-00301.
PY - 2017
Y1 - 2017
N2 - 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. These 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.
AB - 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. These 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.
KW - Biological Event Exploration
KW - Biomedical Entities
KW - Event Clustering
UR - http://www.scopus.com/inward/record.url?scp=85029349186&partnerID=8YFLogxK
U2 - 10.1145/3077136.3084150
DO - 10.1145/3077136.3084150
M3 - Conference contribution
AN - SCOPUS:85029349186
SP - 1277
EP - 1280
BT - SIGIR 2017 - Proceedings of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval
PB - Association for Computing Machinery (ACM)
T2 - 40th International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2017
Y2 - 7 August 2017 through 11 August 2017
ER -