{"file":[{"content_type":"application/pdf","relation":"main_file","access_level":"closed","file_id":"21594","success":1,"date_created":"2021-04-08T08:14:05Z","date_updated":"2021-04-08T08:14:05Z","file_size":512065,"creator":"jkers","file_name":"Kersting-Geierhos2021_Chapter_TowardsAspectExtractionAndClas.pdf"}],"place":"Cham","ddc":["000"],"doi":"10.1007/978-3-030-63787-3_6","abstract":[{"text":"This chapter concentrates on aspect-based sentiment analysis, a form of opinion mining where algorithms detect sentiments expressed about features of products, services, etc. We especially focus on novel approaches for aspect phrase extraction and classification trained on feature-rich datasets. Here, we present two new datasets, which we gathered from the linguistically rich domain of physician reviews, as other investigations have mainly concentrated on commercial reviews and social media reviews so far. To give readers a better understanding of the underlying datasets, we describe the annotation process and inter-annotator agreement in detail. In our research, we automatically assess implicit mentions or indications of specific aspects. To do this, we propose and utilize neural network models that perform the here-defined aspect phrase extraction and classification task, achieving F1-score values of about 80% and accuracy values of more than 90%. As we apply our models to a comparatively complex domain, we obtain promising results. ","lang":"eng"}],"volume":939,"status":"public","author":[{"full_name":"Kersting, Joschka","last_name":"Kersting","id":"58701","first_name":"Joschka"},{"id":"42496","first_name":"Michaela","orcid":"0000-0002-8180-5606","last_name":"Geierhos","full_name":"Geierhos, Michaela"}],"year":"2021","publication_identifier":{"unknown":["978-3-030-63786-6 ; 978-3-030-63787-3"]},"_id":"17905","intvolume":"       939","file_date_updated":"2021-04-08T08:14:05Z","type":"book_chapter","page":"163--189 ","date_created":"2020-08-13T09:29:52Z","publication":"Natural Language Processing in Artificial Intelligence -- NLPinAI 2020","project":[{"name":"SFB 901","_id":"1"},{"_id":"3","name":"SFB 901 - Project Area B"},{"_id":"9","name":"SFB 901 - Subproject B1"}],"department":[{"_id":"579"}],"user_id":"58701","publisher":"Springer","citation":{"mla":"Kersting, Joschka, and Michaela Geierhos. “Towards Aspect Extraction and Classification for Opinion Mining with Deep Sequence Networks.” <i>Natural Language Processing in Artificial Intelligence -- NLPinAI 2020</i>, edited by Roussanka Loukanova, vol. 939, Springer, 2021, pp. 163--189, doi:<a href=\"https://doi.org/10.1007/978-3-030-63787-3_6\">10.1007/978-3-030-63787-3_6</a>.","ieee":"J. Kersting and M. Geierhos, “Towards Aspect Extraction and Classification for Opinion Mining with Deep Sequence Networks,” in <i>Natural Language Processing in Artificial Intelligence -- NLPinAI 2020</i>, vol. 939, R. Loukanova, Ed. Cham: Springer, 2021, pp. 163--189.","apa":"Kersting, J., &#38; Geierhos, M. (2021). Towards Aspect Extraction and Classification for Opinion Mining with Deep Sequence Networks. In R. Loukanova (Ed.), <i>Natural Language Processing in Artificial Intelligence -- NLPinAI 2020</i> (Vol. 939, pp. 163--189). Cham: Springer. <a href=\"https://doi.org/10.1007/978-3-030-63787-3_6\">https://doi.org/10.1007/978-3-030-63787-3_6</a>","short":"J. Kersting, M. Geierhos, in: R. Loukanova (Ed.), Natural Language Processing in Artificial Intelligence -- NLPinAI 2020, Springer, Cham, 2021, pp. 163--189.","ama":"Kersting J, Geierhos M. Towards Aspect Extraction and Classification for Opinion Mining with Deep Sequence Networks. In: Loukanova R, ed. <i>Natural Language Processing in Artificial Intelligence -- NLPinAI 2020</i>. Vol 939. Studies in Computational Intelligence (SCI). Cham: Springer; 2021:163--189. doi:<a href=\"https://doi.org/10.1007/978-3-030-63787-3_6\">10.1007/978-3-030-63787-3_6</a>","chicago":"Kersting, Joschka, and Michaela Geierhos. “Towards Aspect Extraction and Classification for Opinion Mining with Deep Sequence Networks.” In <i>Natural Language Processing in Artificial Intelligence -- NLPinAI 2020</i>, edited by Roussanka Loukanova, 939:163--189. Studies in Computational Intelligence (SCI). Cham: Springer, 2021. <a href=\"https://doi.org/10.1007/978-3-030-63787-3_6\">https://doi.org/10.1007/978-3-030-63787-3_6</a>.","bibtex":"@inbook{Kersting_Geierhos_2021, place={Cham}, series={Studies in Computational Intelligence (SCI)}, title={Towards Aspect Extraction and Classification for Opinion Mining with Deep Sequence Networks}, volume={939}, DOI={<a href=\"https://doi.org/10.1007/978-3-030-63787-3_6\">10.1007/978-3-030-63787-3_6</a>}, booktitle={Natural Language Processing in Artificial Intelligence -- NLPinAI 2020}, publisher={Springer}, author={Kersting, Joschka and Geierhos, Michaela}, editor={Loukanova, RoussankaEditor}, year={2021}, pages={163--189}, collection={Studies in Computational Intelligence (SCI)} }"},"series_title":"Studies in Computational Intelligence (SCI)","editor":[{"full_name":"Loukanova, Roussanka","last_name":"Loukanova","first_name":"Roussanka"}],"date_updated":"2022-01-06T06:53:23Z","has_accepted_license":"1","publication_status":"published","language":[{"iso":"eng"}],"title":"Towards Aspect Extraction and Classification for Opinion Mining with Deep Sequence Networks"}