Article | KEER2014. Proceedings of the 5th Kanesi Engineering and Emotion Research; International Conference; Linköping; Sweden; June 11-13 | Adjective-Based Estimation of Short Sentence’s Impression
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Title:
Adjective-Based Estimation of Short Sentence’s Impression
Author:
Nguyen Thi Thu An: Graduation School of Science and Technology, Keio University, Yokohama, Japan Masafumi Hagiwara: Graduation School of Science and Technology, Keio University, Yokohama, Japan
Download:
Full text (pdf)
Year:
2014
Conference:
KEER2014. Proceedings of the 5th Kanesi Engineering and Emotion Research; International Conference; Linköping; Sweden; June 11-13
Issue:
100
Article no.:
102
Pages:
1219-1234
No. of pages:
16
Publication type:
Abstract and Fulltext
Published:
2014-06-11
ISBN:
978-91-7519-276-5
Series:
Linköping Electronic Conference Proceedings
ISSN (print):
1650-3686
ISSN (online):
1650-3740
Publisher:
Linköping University Electronic Press; Linköpings universitet


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This paper proposes a new method to estimate impression of short sentences considering adjectives. In the proposed system; first; an input sentence is analyzed and preprocessed to obtain keywords. Next; adjectives are taken out from the data which is queried from Google N-gram corpus using keywords-based templates. The semantic similarity scores between the keywords and adjectives are then computed by combining several computational measurements such as Jaccard coefficient; Dice coefficient; Overlap coefficient; and Pointwise mutual information. In the next step; the library sentiment of patterns.en - natural language processing toolkit is utilized to check the sentiment polarity (positive or negative) of adjectives and sentences. Finally; adjectives are ranked and top na adjectives (in this paper na is 5) are chosen according to the estimated values. We carried out subjective experiments and obtained fairly good results. For example; when the input sentence is “It is snowy”; selected adjectives and their scores are: white (0.70); light (0.49); cold (0.43); solid (0.38) and scenic (0.37).

Keywords: Impression; polarity; relatedness; semantic similarity.

KEER2014. Proceedings of the 5th Kanesi Engineering and Emotion Research; International Conference; Linköping; Sweden; June 11-13

Author:
Nguyen Thi Thu An, Masafumi Hagiwara
Title:
Adjective-Based Estimation of Short Sentence’s Impression
References:

Linlin Li; Benjamin Roth; and Caroline Sporleder (2010). Topic models for word sense disambiguation and token-based idiom detection. Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics; (pp. 1138–1147); Uppsala; Sweden: ACL.


Saini; M.; & Sharma; D.; & Gupta; P.K. (2011). Enhancing information retrieval efficiency using semantic-based-combined-similarity-measure. Image Information Processing (ICIIP); International Conference on (pp. 1-4); Waknaghat; India.


Prodromos Malakasiotis (2009). Paraphrase Recognition Using Machine Learning to Combine Similarity Measures. Proceedings of the ACL-IJCNLP 2009 Student Research Workshop (pp. 27-35); Suntec; Singapore.


Ramiz Aliguliyev (2009). A new sentence similarity measure and sentence based extractive technique for automatic text summarization. Expert Systems with Applications; Vol.36; pp.7764–7772.


Jian Hu; Lujun Fang; Yang Cao; Hua-Jun Zeng; Hua Li; Qiang Yang; and Zheng Chen (2008). Enhancing text clustering by leveraging Wikipedia semantics. Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval (pp. 179-186). Pisa; Italy.


Alexander Budanitsky and Graeme Hirst (2006). Evaluating WordNet-based Measures of Lexical Semantic Relatedness. Computational Linguistics; Vol.32; num.1; pp. 13-47.


Mehran Sahami; Timothy Heilman (2006). A web-based kernel function for measuring the similarity of short text snippets. WWW ’06 Proceedings of the 15th international conference on World Wide Web; Vol. 2; (pp. 377 – 386); Edinburgh; Scotland.


Huirong Yang; Pengbin Fu; Baocai Yin; Mengduo Ma; and Yanyan Tang (2011). Computer Software and Applications Conference (COMPSAC) 2011 IEEE 35th Annual; Vol. 69; Munich; Germany.


Danushka Bollegala; Yutaka Matsuo; and Mitsuru Ishizuka (2011). A Web Search Engine-based Approach to Measure Semantic Similarity between Words. Knowledge and Data Engineering; IEEE Transactions on; Vol. 23 (pp.977 – 990).


Michael Strube and Simone Paolo Ponzetto (2006). WikiRelate! computing semantic relatedness using Wikipedia. Proceedings of the 21st national conference on Artificial intelligence - Vol.2 (pp.1419 – 1424). Boston; USA.


Lun-wei Ku and Yong-sheng Lo and Hsin-hsi Chen (2007). Using Polarity Scores of Words for Sentence-level Opinion Extraction. Proceedings of NTCIR-6 Workshop Meeting; May 15-18; Tokyo; Japan; 2007.


Subrahmanian V. S. and Reforgiato Diego (2008). AVA: Adjective-Verb-Adverb Combinations for Sentiment Analysis”; IEEE Intelligent Systems; Vol.23 (pp. 43-50).


Samaneh Moghaddam and Fred Popowich (2010). Opinion Polarity Identifi-cation through Adjectives. CoRR; abs/1011.4623; 2010.


Tim Van de Cruys (2011). Two Multivariate Generalizations of Pointwise Mutual Information”;Proceedings of the Workshop on Distributional Semantics and Compositionality (DiSCo2011); (pp. 26-20).


Aminul Islam and Evangelos Milios and V Keelj (2012). Comparing Word Re-latedness Measures Based on Google n-grams. Proceedings of COLING 2012: Posters (pp.495-506). Mumbai; India.


Kerstin Denecke (2008). Using SentiWordNet for multilingual sentiment analysis. Data Engineering Workshop; ICDEW 2008. IEEE 24th International Conference on; Vol. 72 (pp.507 – 512); Cancún; Mexico.


Hugo Liu ; Push Singh (2004). ConceptNet: A Practical Commonsense Rea-soning Toolkit”; BT TECHNOLOGY JOURNAL; Vol.22 (pp. 211-226).


Rudi Cilibrasi; Paul Vitanyi (2007). The Google Similarity Distance. IEEE Trans. on Knowl. and Data Eng.; Vol. 19 (pp. 370-383).


Rosalind Picard and Jonathan Klein (2002; ScienceDirect). Computers that recognise and respond to user emotion: theoretical and practical implications. Interacting with computers; Vol. 14 (pp.1-20).


Danushka Bollegala; Yutaka Matsuo and Mitsuru Ishizuka (2004). Keyword Extraction From A Single Document Using Word Co-Occurrence Statistical Information”; International Journal on Artificial Intelligence Tools; Vol. 13.


Ulli Waltinger (2009). Polarity reinforcement: Sentiment polarity identification by means of social semantics”; AFRICON; 2009 (pp. 1-6).


Kazuyuki Matsumoto; Junko Minato; Fuji Ren; Shingo Kuroiwa (2005; IEEE). Estimating Human Emotions Using Wording and Sentence Patterns. International Conference on Information Acquisition; (pp. 422-426).


Rosalind Picard (2003). Affective computing: Challenges. International Journal of HumanComputer Studies; Vol.59.


Schumaker; Robert P. and Liu; Ying and Ginsburg; Mark and Chen; Hsinchun (2006). Evaluating mass knowledge acquisition using the ALICE chatterbot: the AZ-ALICE dialog system. Int. J. Hum.-Comput. Stud.; Vol.64 (pp.1132-1140).


Clips; computational linguistics and psycholinguistics research center; http://www.clips.ua.ac.be/pages/pattern-en.

KEER2014. Proceedings of the 5th Kanesi Engineering and Emotion Research; International Conference; Linköping; Sweden; June 11-13

Author:
Nguyen Thi Thu An, Masafumi Hagiwara
Title:
Adjective-Based Estimation of Short Sentence’s Impression
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