DocumentCode
2031620
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
fYear
2015
fDate
20-22 Jan. 2015
Firstpage
7
Lastpage
12
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;
fLanguage
English
Publisher
ieee
Conference_Titel
Mobile Computing and Ubiquitous Networking (ICMU), 2015 Eighth International Conference on
Conference_Location
Hakodate
Type
conf
DOI
10.1109/ICMU.2015.7061020
Filename
7061020
Link To Document