The thesis has researched a set of critical problems in data mining and has proposed four advanced pattern mining algorithm to discover the most interesting and useful data patterns highly relevant to the user's application targets from the data is represented in complex structures.Rong, Jia...
doi:10.1007/978-3-319-14142-8_5AggarwalCharu C.Springer International PublishingAggarwal, C. C. "Association Pattern Mining: Advanced Concepts". In Data Mining, Springer International Publishing, pp. 135-152, 2015.
The papers included in these two volumes cover the following topics: opinion mining, behavior mining, data stream mining, sequential data mining, web mining, image mining, text mining, social network mining, classification, clustering, association rule mining, pattern mining, regression, predication, ...
Microarray Experiments Analysis of Differentially-Expressed Genes Gene-Based Analysis Sample-Based Analysis Pattern-Based Analysis Visualization of Microarray Data New Trends in Mining Gene Expression Microarray Data Readership: Researchers and graduate students in bioinformatics, computational biology and ...
Pattern miningSimilarity searchAdvanced data typesThe complexity of contemporary data warrants a need for better analysing tools in investigative areas. Human processing of data is no longer a viable option. We present an architecture of a novel universal system for analysis of graph-structured data,...
The history can be used for tracking, data warehouse and data mining operations. Tracking and event journals: If messages are retained they can be related to each other. For example: if a message m2 is produced as a result of the consumption of message m1, m1 is related to m2. This ...
Prompt-MolOpt is a tool for molecular optimization; it makes use of prompt-based embeddings, as used in large language models, to improve the transformer’s ability to optimize molecules for specific property adjustments. Notably, Prompt-MolOpt excels in working with limited multiproperty data (...
(BI), to discover deeper insights, make predictions, or generate recommendations. Advanced analytic techniques include those such as data/text mining, machine learning, pattern matching, forecasting, visualization, semantic analysis, sentiment analysis, network and cluster analysis, multivariate statistics,...
Currently, there is an increased need for employing machine learning (ML) and data mining in the healthcare system domain, applications of which play a pivotal role in providing beneficial knowledge to society by utilizing the available data. There are disease risk prediction models that either do...
Professional (🏢): Suitable for practitioners in knowledge discovery, segmentation, and pattern recognition. Official (📜): A classic in the data mining domain, used in many academic courses. Educational (🎓): Provides practical tutorials, bridging the gap between raw data and insights. 10. ...