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| Content Provider | ACM Digital Library |
|---|---|
| Author | Sato, Satoshi Saito, Kuniko Izumi, Tomoko Imamura, Kenji Kikui, Genichiro Asami, Taichi |
| Copyright Year | 2013 |
| Abstract | The growing need for text mining systems, such as opinion mining, requires a deep semantic understanding of the target language. In order to accomplish this, extracting the semantic information of functional expressions plays a crucial role, because functional expressions such as would like to and $\textit{can’t}$ are key expressions to detecting customers’ needs and wants. However, in Japanese, functional expressions appear in the form of suffixes, and two different types of functional expressions are merged into one predicate: one influences the factual meaning of the predicate while the other is merely used for discourse purposes. This triggers an increase in surface forms, which hinders information extraction systems. In this article, we present a novel normalization technique that paraphrases complex functional expressions into simplified forms that retain only the crucial meaning of the predicate. We construct paraphrasing rules based on linguistic theories in syntax and semantics. The results of experiments indicate that our system achieves a high accuracy of 79.7%, while it reduces the differences in functional expressions by up to 66.7%. The results also show an improvement in the performance of predicate extraction, providing encouraging evidence of the usability of paraphrasing as a means of normalizing different language expressions. |
| Starting Page | 1 |
| Ending Page | 20 |
| Page Count | 20 |
| File Format | |
| ISSN | 15300226 |
| e-ISSN | 15583430 |
| DOI | 10.1145/2499955.2499959 |
| Volume Number | 12 |
| Issue Number | 3 |
| Journal | ACM Transactions on Asian Language Information Processing (TALIP) |
| Language | English |
| Publisher | Association for Computing Machinery (ACM) |
| Publisher Date | 2013-08-01 |
| Publisher Place | New York |
| Access Restriction | One Nation One Subscription (ONOS) |
| Subject Keyword | Paraphrasing Factuality analysis Functional expressions Linguistic theories Opinion mining Sentiment analysis Text mining |
| Content Type | Text |
| Resource Type | Article |
| Subject | Computer Science |
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