{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,13]],"date-time":"2026-05-13T08:32:21Z","timestamp":1778661141303,"version":"3.51.4"},"reference-count":27,"publisher":"SAGE Publications","issue":"1","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IFS"],"published-print":{"date-parts":[[2022,6,1]]},"abstract":"<jats:p>The refining of information from the immense amount of unstructured data on the internet can be a critical issue in identifying public opinion. It is difficult to extract relevant concepts from huge amounts of data. Concept level semantic parsing is improved over word-based investigation as it conserves the semantical data relevant to many-word articulations. The semantic proposals offer a superior comprehension of textual data and serve to altogether precision the exactness of numerous mining operations in text assignments. The extraction of concepts from textual data is a significant step forward in content analysis at the concept stage. We present a CLSA-CapsNet method that extracts concepts from natural language text. Then the extracted concepts are applied in Capsule networks (CapsNet). Moreover, the integration of Concept Level Sentiment Analysis (CLSA) and Capsule Networks (CapsNet) has not yet been implemented on the hotel review dataset. This is the first attempt, which we researched and embraced by the capsule network, to develop classification models for hotel reviews. The developed results demonstrated excellent performance with a prediction accuracy of 86.6% for CLSA-CapsNet models, respectively. Various similarities have also been made across our techniques and they are implemented by some other deep learning algorithms, such as rnn-lstm. Overall, the outstanding success obtained by CLSA-CapsNet in this investigation highlights its ability in the hotel review dataset. We likewise show exploratory outcomes, in which the proposed system outpaced the state-of-the-art CLSA-CapsNet model.<\/jats:p>","DOI":"10.3233\/jifs-211321","type":"journal-article","created":{"date-parts":[[2022,4,5]],"date-time":"2022-04-05T11:10:06Z","timestamp":1649157006000},"page":"107-123","source":"Crossref","is-referenced-by-count":8,"title":["CLSA-CapsNet: Dependency based concept level sentiment analysis for text"],"prefix":"10.1177","volume":"43","author":[{"given":"P.D.","family":"Mahendhiran","sequence":"first","affiliation":[{"name":"Department of Computer Science and Business Systems, Sri Krishna College of Engineering and Technology, Coimbatore, Tamil Nadu, India"}]},{"given":"Kannimuthu","family":"Subramanian","sequence":"additional","affiliation":[{"name":"Department of Information Technology, Karpagam College of Engineering, Coimbatore, Tamil Nadu, India"}]}],"member":"179","reference":[{"issue":"4","key":"10.3233\/JIFS-211321_ref1","doi-asserted-by":"crossref","first-page":"477","DOI":"10.1007\/s12559-012-9145-4","article-title":"Sentic album: content-, concept-, and context-based online personal photo management system","volume":"4","author":"Cambria","year":"2012","journal-title":"Cognitive Computation"},{"key":"10.3233\/JIFS-211321_ref2","doi-asserted-by":"crossref","first-page":"104","DOI":"10.1016\/j.neunet.2014.10.005","article-title":"Towards an intelligent framework for multimodal affective data analysis","volume":"63","author":"Poria","year":"2015","journal-title":"Neural Networks"},{"issue":"1","key":"10.3233\/JIFS-211321_ref3","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/2192-1962-3-9","article-title":"Intention awareness: improving upon situation awareness in human-centric environments","volume":"3","author":"Howard","year":"2013","journal-title":"Human-centric Computing and Information Sciences"},{"key":"10.3233\/JIFS-211321_ref5","first-page":"1","article-title":"Towards crowd validation of the UK national health service","volume":"10","author":"Cambria","year":"2010","journal-title":"WebSci"},{"key":"10.3233\/JIFS-211321_ref7","doi-asserted-by":"crossref","first-page":"102281","DOI":"10.1016\/j.simpat.2021.102281","article-title":"Modeling and simulation of urban air quality with a 2-phase assessment technique","volume":"109","author":"Raheja","year":"2021","journal-title":"Simulation Modelling Practice and Theory"},{"issue":"1","key":"10.3233\/JIFS-211321_ref8","doi-asserted-by":"crossref","first-page":"1","DOI":"10.2200\/S00416ED1V01Y201204HLT016","article-title":"Sentiment analysis and opinion mining","volume":"5","author":"Liu","year":"2012","journal-title":"Synthesis Lectures on Human Language Technologies"},{"key":"10.3233\/JIFS-211321_ref11","doi-asserted-by":"crossref","unstructured":"Cambria E. , et al., Common sense computing: From the society of mind to digital intuition and beyond, European Workshop on Biometrics and Identity Management. 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