Abstract
In recent years, microblogging services have become very popular. The larger volume of real-time information generated by millions of users, more important to extract useful information from the microblogging services will be. In this work, we want to use opinion mining to find the relevant and significant features of items from the microblogging services, like Twitter. We construct a sentiment-based framework to identify the relevant features in microblogging. Our method consists of two stages. First, the data process stage processes the raw data from microblogging services. Then, in second stage we extract the relevant features by the sentiment characteristics from these messages and utilize these extracted features to construct the relevant feature network and group them according their concepts relations. Therefore, our system could be applied for knowing the characteristics of a product quickly and explicitly. In our experiments, our system can identify the popular item features in different domains effectively and the same concept features can cluster together in small groups.
| Original language | English |
|---|---|
| Title of host publication | TAAI 2015 - 2015 Conference on Technologies and Applications of Artificial Intelligence |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 396-403 |
| Number of pages | 8 |
| ISBN (Electronic) | 9781467396066 |
| DOIs | |
| Publication status | Published - 2016 Feb 12 |
| Event | Conference on Technologies and Applications of Artificial Intelligence, TAAI 2015 - Tainan, Taiwan Duration: 2015 Nov 20 → 2015 Nov 22 |
Publication series
| Name | TAAI 2015 - 2015 Conference on Technologies and Applications of Artificial Intelligence |
|---|
Other
| Other | Conference on Technologies and Applications of Artificial Intelligence, TAAI 2015 |
|---|---|
| Country | Taiwan |
| City | Tainan |
| Period | 15-11-20 → 15-11-22 |
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All Science Journal Classification (ASJC) codes
- Artificial Intelligence
- Computer Science Applications
Cite this
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Identification of item features in microblogging data. / Huang, Shih Ting; Li, Pei Shu; Kao, Hung-Yu.
TAAI 2015 - 2015 Conference on Technologies and Applications of Artificial Intelligence. Institute of Electrical and Electronics Engineers Inc., 2016. p. 396-403 7407082 (TAAI 2015 - 2015 Conference on Technologies and Applications of Artificial Intelligence).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
TY - GEN
T1 - Identification of item features in microblogging data
AU - Huang, Shih Ting
AU - Li, Pei Shu
AU - Kao, Hung-Yu
PY - 2016/2/12
Y1 - 2016/2/12
N2 - In recent years, microblogging services have become very popular. The larger volume of real-time information generated by millions of users, more important to extract useful information from the microblogging services will be. In this work, we want to use opinion mining to find the relevant and significant features of items from the microblogging services, like Twitter. We construct a sentiment-based framework to identify the relevant features in microblogging. Our method consists of two stages. First, the data process stage processes the raw data from microblogging services. Then, in second stage we extract the relevant features by the sentiment characteristics from these messages and utilize these extracted features to construct the relevant feature network and group them according their concepts relations. Therefore, our system could be applied for knowing the characteristics of a product quickly and explicitly. In our experiments, our system can identify the popular item features in different domains effectively and the same concept features can cluster together in small groups.
AB - In recent years, microblogging services have become very popular. The larger volume of real-time information generated by millions of users, more important to extract useful information from the microblogging services will be. In this work, we want to use opinion mining to find the relevant and significant features of items from the microblogging services, like Twitter. We construct a sentiment-based framework to identify the relevant features in microblogging. Our method consists of two stages. First, the data process stage processes the raw data from microblogging services. Then, in second stage we extract the relevant features by the sentiment characteristics from these messages and utilize these extracted features to construct the relevant feature network and group them according their concepts relations. Therefore, our system could be applied for knowing the characteristics of a product quickly and explicitly. In our experiments, our system can identify the popular item features in different domains effectively and the same concept features can cluster together in small groups.
UR - http://www.scopus.com/inward/record.url?scp=84964265773&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84964265773&partnerID=8YFLogxK
U2 - 10.1109/TAAI.2015.7407082
DO - 10.1109/TAAI.2015.7407082
M3 - Conference contribution
AN - SCOPUS:84964265773
T3 - TAAI 2015 - 2015 Conference on Technologies and Applications of Artificial Intelligence
SP - 396
EP - 403
BT - TAAI 2015 - 2015 Conference on Technologies and Applications of Artificial Intelligence
PB - Institute of Electrical and Electronics Engineers Inc.
ER -