Emerging Technologies of Text Mining: Techniques and Applications: Techniques and Applicationsdo Prado, Hercules Antonio, Ferneda, Edilson IGI Global, 2007 M10 31 - 376 páginas Massive amounts of textual data make up most organizations' stored information. Therefore, there is increasingly high demand for a comprehensive resource providing practical hands-on knowledge for real-world applications. Emerging Technologies of Text Mining: Techniques and Applications provides the most recent technical information related to the computational models of the text mining process, discussing techniques within the realms of classification, association analysis, information extraction, and clustering. Offering an innovative approach to the utilization of textual information mining to maximize competitive advantage, Emerging Technologies of Text Mining: Techniques and Applications will provide libraries with the defining reference on this topic. |
Dentro del libro
Resultados 1-5 de 81
... is derived. Experimental results show that the derived taxonomy can demonstrate how the information is interwoven in a comprehensive and concise form. Chapter VI Rule Discovery from Textual Data / Shigeaki Sakurai ...
... -mail classification, and show experimental results found by analyzing academic and newsgroup related texts. Chapter VIII A Multi-Agent Neural Network System for Web Text Mining / Lean Yu, Shouyang Wang, and Kin Keung Lai ...
... show that the derived taxonomy can demonstrate how the information is interwoven in a comprehensive and concise form. Chapter VI brings an original approach to knowledge discovery from textual data based on a fuzzy decision tree. The ...
... shows an example of the tagging rule. The first column represents a sequence of words. The second to the fifth columns represent PartOf-Speech, Word type, Lookup in a dictionary, and Name Entity Recognition results of the word sequence ...
... shows the learning algorithm in BWI. In BWI, AdaBoost algorithm runs in iterations. In each iteration, it outputs a weak learner (called hypotheses) from the training data and also a weight for the learner representing the percentage of ...
Contenido
1 | |
Creating Strategic Information for Organizations with Structured Text | 34 |
Automatic NLP for Competitive Intelligence | 54 |
Mining Profiles and Definitions with Natural Language Processing | 77 |
Deriving Taxonomy from Documents at Sentence Level | 99 |
Rule Discovery from Textual Data | 120 |
Exploring Unclassified Texts Using Multiview Semisupervised Learning | 139 |
A MultiAgent Neural Network System for Web Text Mining | 162 |
AntWebWeb Search Based on Ant Behavior Approach and Implementation in Case of Interlegis | 208 |
Conceptual Clustering of Textual Documents and Some Insights for Knowledge Discovery | 223 |
A Hierarchical Online Classifier for Patent Categorization | 244 |
Text Mining to Define a Validated Model of Hospital Rankings | 268 |
An Interpretation Process for Clustering Analysis Based on the Ontology of Language | 297 |
Compilation of References | 321 |
About the Contributors | 348 |
Index | 355 |
Otras ediciones - Ver todas
Emerging Technologies of Text Mining: Techniques and Applications Hercules Antonio do Prado,Edilson Ferneda Sin vista previa disponible - 2008 |