Short Text Topic Modeling to Identify Trends on Wearable Bio-sensors in Different Media TypesVise andre og tillknytning
2019 (engelsk)Inngår i: Proceedings - 6th International Symposium on Computational and Business Intelligence, ISCBI 2018, IEEE Computer Society, 2019, s. 89-93Konferansepaper, Publicerat paper (Fagfellevurdert)
Abstract [en]
The technology and techniques for bio-sensors are rapidly evolving. Accordingly, there is significant business interest to identify upcoming technologies and new targets for the near future. Text information from internet reflects much of the recent information and public interests that help to understand the trend of a certain field. Thus, we utilize Dirichlet process topic modeling on different media sources containing short text (e.g., blogs, news) which is able to self-adapt the learned topic space to the data. We share the observations from the domain experts on the results derived from topic modeling on wearable biosensors from multiple media sources over more than eight years. We analyze the topics on wearable devices, forecast and market analysis, and bio-sensing techniques found from our method.
sted, utgiver, år, opplag, sider
IEEE Computer Society, 2019. s. 89-93
Emneord [en]
Bayesian non-parametrics, Bio-sensor, short text, topic modeling, wearable, Biosensors, Information analysis, Bayesian nonparametrics, Dirichlet process, Market analysis, Short texts, Text information, Wearable devices, Wearable sensors
HSV kategori
Forskningsprogram
Skövde Artificial Intelligence Lab (SAIL)
Identifikatorer
URN: urn:nbn:se:his:diva-16746DOI: 10.1109/ISCBI.2018.00027ISI: 000462379700017Scopus ID: 2-s2.0-85063041846ISBN: 978-1-5386-9450-3 (digital)ISBN: 978-1-5386-9451-0 (tryckt)OAI: oai:DiVA.org:his-16746DiVA, id: diva2:1302771
Konferanse
ISCBI 2018 : 2018 6th International Symposium on Computational and Business Intelligence. Basel, Switzerland August 22 - 29 2018
2019-04-052019-04-052025-09-29bibliografisk kontrollert