{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T04:07:52Z","timestamp":1760242072775,"version":"build-2065373602"},"reference-count":27,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2018,11,29]],"date-time":"2018-11-29T00:00:00Z","timestamp":1543449600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100004595","name":"Universiti Sains Malaysia","doi-asserted-by":"publisher","award":["1001\/PKOMP\/811335"],"award-info":[{"award-number":["1001\/PKOMP\/811335"]}],"id":[{"id":"10.13039\/501100004595","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Informatics"],"abstract":"<jats:p>Online reviews are an important source of opinion to measure products\u2019 quality. Hence, automated opinion mining is used to extract important features (aspect) and related comments (sentiment). Extraction of correct aspect-sentiment pairs is critical for overall outcome of opinion mining; however, current works still have limitations in terms of identifying special compound noun and parent-child relationship aspects in the extraction process. To address these problems, an aspect-sentiment pair extraction using the rules and compound noun lexicon (ASPERC) model is proposed. The model consists of three main phases, such as compound noun lexicon generation, aspect-sentiment pair rule generation, and aspect-sentiment pair extraction. The combined approach of rules generated from training sentences and domain specific compound noun lexicon enable extraction of more aspects by firstly identifying special compound noun and parent-child aspects, which eventually contribute to more aspect-sentiment pair extraction. The experiment is conducted with the SemEval 2014 dataset to compare proposed and baseline models. Both ASPERC and its variant, ASPER, result higher in recall (28.58% and 22.55% each) compared to baseline and satisfactorily extract more aspect sentiment pairs. Lastly, the reasonable outcome of ASPER indicates applicability of rules to various domains.<\/jats:p>","DOI":"10.3390\/informatics5040045","type":"journal-article","created":{"date-parts":[[2018,11,29]],"date-time":"2018-11-29T11:47:53Z","timestamp":1543492073000},"page":"45","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":10,"title":["Domain-Specific Aspect-Sentiment Pair Extraction Using Rules and Compound Noun Lexicon for Customer Reviews"],"prefix":"10.3390","volume":"5","author":[{"given":"Noor Rizvana","family":"Ahamed Kabeer","sequence":"first","affiliation":[{"name":"School of Computer Sciences, Universiti Sains Malaysia, Penang 11800, Malaysia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2972-3523","authenticated-orcid":false,"given":"Keng Hoon","family":"Gan","sequence":"additional","affiliation":[{"name":"School of Computer Sciences, Universiti Sains Malaysia, Penang 11800, Malaysia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Erum","family":"Haris","sequence":"additional","affiliation":[{"name":"School of Computer Sciences, Universiti Sains Malaysia, Penang 11800, Malaysia"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2018,11,29]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1007\/978-3-031-02145-9","article-title":"Sentiment analysis and opinion mining","volume":"Volume 5","author":"Liu","year":"2012","journal-title":"Synthesis Lectures on Human Language Technologies"},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Perikos, I., and Hatzilygeroudis, I. (2017, January 24\u201326). Aspect based sentiment analysis in social media with classifier ensembles. Proceedings of the IEEE\/ACIS 16th International Conference on Computer and Information Science (ICIS), Wuhan, China.","DOI":"10.1109\/ICIS.2017.7960005"},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Hu, M., and Liu, B. (2004, January 22\u201324). Mining and summarizing customer reviews. Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Seattle, WA, USA.","DOI":"10.1145\/1014052.1014073"},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Popescu, A.M., and Etzioni, O. (2007). Extracting product features and opinions from reviews. Natural Language Processing and Text Mining, Springer.","DOI":"10.1007\/978-1-84628-754-1_2"},{"key":"ref_5","unstructured":"Moghaddam, S., and Ester, M. (November, January 29). On the Design of LDA Models for Aspect-based Opinion Mining. Proceedings of the 12th ACM International Conference on Information & Knowledge Management, Maui, HI, USA."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"69","DOI":"10.5121\/ijwest.2012.3407","article-title":"Web User Opinion Analysis for Product Features Extraction and Opinion Summarization","volume":"3","author":"Ravi","year":"2012","journal-title":"Int. J. Web Semant. Technol."},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Chinsha, T.C., and Shibily, J. (2015, January 4\u20135). A Syntactic Approach for Aspect Based Opinion Mining. Proceedings of the 9th International Workshop on Semantic Evaluation, Denver, CO, USA.","DOI":"10.1109\/ICOSC.2015.7050774"},{"key":"ref_8","unstructured":"Bancken, W., Alfarone, D., and Davis, J. (2014, January 15). Automatically Detecting and Rating Product Aspects from Textual Customer Reviews. Proceedings of the DMNLP, Workshop at ECML\/PKDD, Nancy, France."},{"key":"ref_9","unstructured":"Bross, J., and Ehrig, H. (November, January 27). Automatic construction of domain and aspect specific sentiment lexicons for customer review mining. Proceedings of the 22nd ACM International Conference on Information & Knowledge Management, San Francisco, CA, USA."},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Veselovsk\u00e1, K., and Tamchyna, A. (2014, January 23\u201324). UFAL: Using Hand-crafted Rules in Aspect Based Sentiment Analysis on Parsed Data. Proceedings of the 8th International Workshop on Semantic Evaluation, Dublin, Ireland.","DOI":"10.3115\/v1\/S14-2124"},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Poria, S., Cambria, E., Gelbukh, A., and Gui, C. (2014, January 24). A Rule-Based Approach to Aspect Extraction from Product Reviews. Proceedings of the Second Workshop on Natural Language Processing for Social Media, Dublin, Ireland.","DOI":"10.3115\/v1\/W14-5905"},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Zhao, Q., Wang, H., Lv, P., and Zhang, C. (2014, January 3\u20137). A Bootstrapping Based Refinement Framework for Mining Opinion Words and Targets. Proceedings of the 23rd ACM International Conference On Conference On Information and Knowledge Management, Shanghai, China.","DOI":"10.1145\/2661829.2662069"},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Carpenter, T., Golab, L., and Syed, S. (2014, January 11\u201313). Is the Grass Greener? Mining Electric Vehicle Opinions. Proceedings of the 5th International Conference on Future Energy Systems, Cambridge, UK.","DOI":"10.1145\/2602044.2602050"},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Li, Y., Wang, H., Qin, Z., Xu, W., and Guo, J. (2014, January 24\u201328). Confidence Estimation and Reputation Analysis in Aspect Extraction. Proceedings of the 22nd International Conference on Pattern Recognition, Stockholm, Sweden.","DOI":"10.1109\/ICPR.2014.621"},{"key":"ref_15","unstructured":"Kim, H., Ganesan, K., Parikshit, S., and ChengXiang, Z. (2011). Comprehensive review of opinion summarization, in press."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"813","DOI":"10.1109\/TKDE.2015.2485209","article-title":"Survey on Aspect-Level Sentiment Analysis","volume":"28","author":"Schouten","year":"2016","journal-title":"IEEE T Knowl. Data En."},{"key":"ref_17","unstructured":"Hurford, J.R. (1994). Grammar: A. Student\u2019s Guide, Cambridge University Press."},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Kim, S., Zhang, J., Chen, Z., Oh, A., and Liu, S. (2013, January 14\u201318). A Hierarchical Aspect-Sentiment Model for Online Reviews. Proceedings of the 27th AAAI Conference on Artifical Intelligence, Bellevue, WA, USA.","DOI":"10.1609\/aaai.v27i1.8700"},{"key":"ref_19","unstructured":"Xu, P., Kang, J., Ringgaard, M., and Och, F. (June, January 31). Using a Dependency Parser to Improve SMT for Subject-Object-Verb Languages. Proceedings of the Annual Conference of the North American Chapter of ACL, Boulder, CO, USA."},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Wang, W., Pan, S.J., Dahlmeier, D., and Xiao, X. (2017, January 4\u20139). Coupled Multi-Layer Attentions for Co-Extraction of Aspect and Opinion Terms. Proceedings of the AAAI, San Francisco, CA, USA.","DOI":"10.1609\/aaai.v31i1.10974"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"288","DOI":"10.1002\/asi.5090110403","article-title":"Key word-in-context index for technical literature (KWIC index)","volume":"11","author":"Luhn","year":"1960","journal-title":"Am. Doc."},{"key":"ref_22","unstructured":"Anthony, L. (2005, January 10\u201313). AntConc: Design and Development of a Freeware Corpus Analysis Toolkit for the Technical Writing Classroom. Proceedings of the 2005 International Professional Communication Conference, Limerick, Ireland."},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Barri\u2019ere, C., and M\u00e9nard, P. (2014, January 24). Multiword noun compound bracketing using Wikipedia. Proceedings of the First Workshop on Computational Approaches to Compound Analysis, Dublin, Ireland.","DOI":"10.3115\/v1\/W14-5708"},{"key":"ref_24","unstructured":"Jurafsky, D., and Martin, J.H. (2014). Speech and Language Processing: An Introduction to Natural Language Processing, Computational Linguistics, And Speech Recognition, Prentice Hall PTR. [2nd ed.]."},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Pontiki, M., Galanis, D., Pavlopoulos, J., Papageorgiou, H., Androutsopoulos, I., and Manandhar, S. (2014, January 23\u201324). Semeval-2014 Task 4: Aspect Based Sentiment Analysis. Proceedings of the 8th International Workshop on Semantic Evaluation, Dublin, Ireland.","DOI":"10.3115\/v1\/S14-2004"},{"key":"ref_26","unstructured":"Ganu, G., Elhadad, N., and Marian, A. (2009, January 28). Beyond the Stars: Improving Rating Predictions using Review Text Content. Proceedings of the 12th International Workshop on the Web and Databases, Providence, RI, USA."},{"key":"ref_27","unstructured":"Kiremire, A.R. (2011). The Application of The Pareto Principle in Software Engineering, Louisiana Tech University."}],"container-title":["Informatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2227-9709\/5\/4\/45\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T15:33:25Z","timestamp":1760196805000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2227-9709\/5\/4\/45"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,11,29]]},"references-count":27,"journal-issue":{"issue":"4","published-online":{"date-parts":[[2018,12]]}},"alternative-id":["informatics5040045"],"URL":"https:\/\/doi.org\/10.3390\/informatics5040045","relation":{},"ISSN":["2227-9709"],"issn-type":[{"type":"electronic","value":"2227-9709"}],"subject":[],"published":{"date-parts":[[2018,11,29]]}}}