Data mining for service / Katsutoshi Yada, editor. - Heidelberg : Springer, c2014. - viii, 291 p. : ill., charts. - Studies in big data ; v. 3 . - Studies in big data ; v. 3 .

Data mining for service -- Feature selection over distributed data streams -- Learning hidden Markov models using probabilistic matrix factorization -- Dimensionality reduction for information retrieval using vector replacement of rare terms -- Panel data analysis via variable selection and subject clustering -- A weighted density-based approach for identifying standardized items that are significantly related to the biological literature -- Nonnegative tensor factorization of biomedical literature for analysis of genomic data -- Text mining of business-oriented conversations at a call center -- Scam detection in twitter -- A matrix factorization framework for jointly analyzing multiple nonnegative data sources -- Recommendation systems for web 2.0 marketing -- Handling imbalanced and overlapping classes in smart environments prompting dataset -- Change detection from heterogeneous data sources -- Interesting subset discovery and its application on service processes -- Text document cluster analysis through visualization of 3D projections.

Y58 M07 BKE

9783642452512 (pbk.)


Big data
Data mining

006.312 / D232