TY - CHAP U1 - Konferenzveröffentlichung A1 - Wiegand, Michael A1 - Klakow, Dietrich ED - Lane, H. Chad ED - Guesgen, Hans W. T1 - The Role of Knowledge-based Features in Polarity Classification at Sentence Level T2 - Proceedings of the Twenty-Second International Florida Artificial Intelligence Research Society Conference, 19–21 May 2009, Sanibel Island, Florida, USA N2 - Though polarity classification has been extensively explored at document level, there has been little work investigating feature design at sentence level. Due to the small number of words within a sentence, polarity classification at sentence level differs substantially from document-level classification in that resulting bag-of-words feature vectors tend to be very sparse resulting in a lower classification accuracy. In this paper, we show that performance can be improved by adding features specifically designed for sentence-level polarity classification. We consider both explicit polarity information and various linguistic features. A great proportion of the improvement that can be obtained by using polarity information can also be achieved by using a set of simple domain-independent linguistic features. KW - Computerlinguistik KW - Text Mining KW - Polarität KW - Natürliche Sprache KW - Sentimentanalyse Y1 - 2009 U6 - https://nbn-resolving.org/urn:nbn:de:bsz:mh39-84390 UN - https://nbn-resolving.org/urn:nbn:de:bsz:mh39-84390 UR - https://www.aaai.org/ocs/index.php/FLAIRS/2009/paper/view/24 SN - 978-1-57735-419-2 SB - 978-1-57735-419-2 SP - 296 EP - 301 PB - AAAI Press CY - Menlo Park, CA ER -