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Opinion Marks : A Human-Based Computation Approach to Instill Structure into Unstructured Text on the Web

Opinion Marks : A Human-Based Computation Approach to Instill Structure into Unstructured Text on the Web

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KWON, Bum Chul, Jaegul CHOO, Sung-Hee KIM, Daniel KEIM, Haesun PARK, Ji Soo YI, 2015. Opinion Marks : A Human-Based Computation Approach to Instill Structure into Unstructured Text on the Web. KDD 2015 Workshop on Interactive Data Exploration and Analytics (IDEA’15). Sydney, 13. Aug 2015. In: POLO CHAU, , ed. and others. Proceedings of the ACM SIGKDD Workshop on Interactive Data Exploration and Analytics Permission. New York:ACM, pp. 47-55

@inproceedings{Kwon2015Opini-32597, title={Opinion Marks : A Human-Based Computation Approach to Instill Structure into Unstructured Text on the Web}, url={http://poloclub.gatech.edu/idea2015/papers/p47-kwon.pdf}, year={2015}, address={New York}, publisher={ACM}, booktitle={Proceedings of the ACM SIGKDD Workshop on Interactive Data Exploration and Analytics Permission}, pages={47--55}, editor={Polo Chau}, author={Kwon, Bum Chul and Choo, Jaegul and Kim, Sung-Hee and Keim, Daniel and Park, Haesun and Yi, Ji Soo} }

Kim, Sung-Hee Yi, Ji Soo Despite recent improvements in computational approaches such as<br />machine learning, natural language processing, and computational<br />linguistics, making a computer understand human-generated unstructured<br />text still remains a difficult problem to solve. To alleviate<br />the challenges, we propose an approach called “Opinion Marks,”<br />which enables writers to mark positive and negative aspects of a<br />topic on their own text. In addition, Opinion Marks incorporates an<br />automatic marking suggestion algorithm to offload a user’s marking<br />effort. The phrases marked with Opinion Marks can be further<br />used to clarify the sentiments of other text in a similar context.<br />We implemented Opinion Marks at a question answering website<br />http://caniask.net. To test the efficacy of Opinion Marks, we<br />conducted a crowdsourced experiment with 144 participants in a<br />between-subject design under three different conditions: 1) human<br />marking only; 2) machine marking only (automatic marking suggestion);<br />and 3) human-machine collaboration (Opinion Marks).<br />This study revealed that Opinion Marks significantly improves the<br />quality of marked phrases and usability of the system. Park, Haesun eng terms-of-use 2016-01-15T08:33:21Z Choo, Jaegul 2016-01-15T08:33:21Z Opinion Marks : A Human-Based Computation Approach to Instill Structure into Unstructured Text on the Web Kim, Sung-Hee Keim, Daniel Park, Haesun Choo, Jaegul 2015 Kwon, Bum Chul Keim, Daniel Yi, Ji Soo Kwon, Bum Chul

Dateiabrufe seit 15.01.2016 (Informationen über die Zugriffsstatistik)

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