Multi-Relational Data Mining
by Arno Jan Knobbe
Publisher: IOS Press 2006
Number of pages: 130
This thesis is concerned with Data Mining: extracting useful insights from large and detailed collections of data. With the increased possibilities in modern society for companies and institutions to gather data cheaply and efficiently, this subject has become of increasing importance.
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by I. Androutsopoulos, G. D. Ritchie, P. Thanisch - arXiv
This paper is an introduction to natural language interfaces to databases (NLIDBs). Some advantages and disadvantages of NLIDBs are then discussed, comparing NLIDBs to formal query languages, form-based interfaces, and graphical interfaces.
by Julio Ponce, Adem Karahoca - InTech
This book presents different ways of theoretical and practical advances and applications of data mining in different promising areas. The book will serve as a Data Mining bible to show a right way for the students, researchers and practitioners.
by Kyriacos E. Pavlou, Richard T. Snodgrass - University of Arizona
The text on detection via cryptographic hashing. The authors show how to determine when the tampering occurred, what data was tampered, and who did the tampering. Four successively more sophisticated forensic analysis algorithms are presented.
by Shigeaki Sakurai (ed.) - InTech
Text mining techniques are studied aggressively in order to extract the knowledge from the data. This book introduces advanced text mining techniques. They are various techniques from relation extraction to under or less resourced language.