Title :
Extracting local event information from micro-blogs for trip planning
Author :
Yamada, Wataru ; Torii, Daisuke ; Kikuchi, Haruka ; Inamura, Hiroshi ; Ochiai, Keiichi ; Ohta, Ken
Author_Institution :
NTT Docomo Inc., Yokosuka, Japan
Abstract :
This paper describes a method to extract local event information from the micro-blog service Twitter. Twitter holds innumerable user-posted short messages called tweets that cover various topics including local events. Our proposal is composed of three steps: 1) extract tweets related to local events from local tweets by the Support Vector Machine (SVM) approach, 2) identify and extract the venues, names and times of local events mentioned in the tweets by applying Conditional Random Fields (CRF), 3) use the venues and similarity of names to aggregate duplicate local event information. We implement the proposed method and confirm that it extracts local event information with higher precision than the conventional methods.
Keywords :
information needs; information networks; information retrieval; social networking (online); support vector machines; CRF; SVM; conditional random fields; innumerable user-posted short messages; local event information; local tweets; microblog service Twitter; microblogs; support vector machine; trip planning; Aggregates; Data mining; Feature extraction; Hidden Markov models; Support vector machines; Training data; Twitter; Twitter; local event; local information service; machine learning; natural language processing;
Conference_Titel :
Mobile Computing and Ubiquitous Networking (ICMU), 2015 Eighth International Conference on
Conference_Location :
Hakodate
DOI :
10.1109/ICMU.2015.7061020