{"title":"An Approach for Analyzing Unstructured Text Data Using Topic Modeling Techniques for Efficient Information Extraction","authors":"A. Zadgaonkar, A. Agrawal","doi":"10.1007/s00354-023-00230-5","DOIUrl":null,"url":null,"abstract":"","PeriodicalId":54726,"journal":{"name":"New Generation Computing","volume":" ","pages":""},"PeriodicalIF":2.0000,"publicationDate":"2023-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"New Generation Computing","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.1007/s00354-023-00230-5","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"COMPUTER SCIENCE, HARDWARE & ARCHITECTURE","Score":null,"Total":0}
期刊介绍：
The journal is specially intended to support the development of new computational and cognitive paradigms stemming from the cross-fertilization of various research fields. These fields include, but are not limited to, programming (logic, constraint, functional, object-oriented), distributed/parallel computing, knowledge-based systems, agent-oriented systems, and cognitive aspects of human embodied knowledge. It also encourages theoretical and/or practical papers concerning all types of learning, knowledge discovery, evolutionary mechanisms, human cognition and learning, and emergent systems that can lead to key technologies enabling us to build more complex and intelligent systems. The editorial board hopes that New Generation Computing will work as a catalyst among active researchers with broad interests by ensuring a smooth publication process.
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