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. |
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... possible. In this way, the complexity involved in processing the huge amount of texts available in the organizations can be effectively approached. Drs. Edilson Ferneda and Hércules Prado, since 2002, have carried out methodological and ...
... possible due to the most recent advances in its realm. The complexity inherent to the enormous and increasing amount of textual data can now be effectively approached, what enables the discovery of interesting relations in documents, e ...
... possible to carry out. First, we want to thank the authors that submitted their contributions, accepted or not, by putting their efforts and commitment in this project. At this point, it is important to say that, in face of the ...
... possible extractions: “Professor Steve Skiena” and “Steve Skiena”. The histogram model estimates confidence as Cs * Ce * P(|e - s|). Here Cs is the confidence of the start prediction and Ce is the confidence of the end prediction. (For ...
... possible to find the sequence of POS tags that best accounts for any given sentence by identifying the sequence of states most likely to have been traversed when “generating” that sequence of words. The states in an HMM are considered ...
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 |