By Xudong Luo, Jeffrey Xu Yu, Zhi Li
This booklet constitutes the complaints of the tenth overseas convention on complicated info Mining and functions, ADMA 2014, held in Guilin, China in the course of December 2014. The forty eight normal papers and 10 workshop papers offered during this quantity have been rigorously reviewed and chosen from ninety submissions. They care for the subsequent subject matters: facts mining, social community and social media, suggest structures, database, dimensionality relief, strengthen laptop studying suggestions, category, great info and purposes, clustering equipment, computing device studying, and information mining and database.
Read Online or Download Advanced Data Mining and Applications: 10th International Conference, ADMA 2014, Guilin, China, December 19-21, 2014. Proceedings PDF
Best data mining books
A palms on consultant to net scraping and textual content mining for either rookies and skilled clients of R Introduces primary suggestions of the most structure of the internet and databases and covers HTTP, HTML, XML, JSON, SQL.
Provides simple recommendations to question internet records and knowledge units (XPath and average expressions). an intensive set of routines are awarded to lead the reader via each one method.
Explores either supervised and unsupervised options in addition to complex options akin to facts scraping and textual content administration. Case reviews are featured all through in addition to examples for every process awarded. R code and suggestions to workouts featured within the ebook are supplied on a assisting web site.
This Springer short presents a entire review of the historical past and up to date advancements of huge info. the price chain of massive information is split into 4 stages: facts new release, facts acquisition, info garage and information research. for every part, the ebook introduces the overall history, discusses technical demanding situations and stories the newest advances.
This publication constitutes the refereed court cases of the twenty sixth Australasian Database convention, ADC 2015, held in Melbourne, VIC, Australia, in June 2015. The 24 complete papers provided including five demo papers have been conscientiously reviewed and chosen from forty three submissions. The Australasian Database convention is an annual foreign discussion board for sharing the newest learn developments and novel functions of database platforms, information pushed functions and knowledge analytics among researchers and practitioners from world wide, fairly Australia and New Zealand.
- Design Thinking Business Analysis: Business Concept Mapping Applied
- Spark for Data Science
- Advances in intelligent information and database systems
- Mining of Data with Complex Structures
- Fuzzy Databases: Modeling, Design And Implementation
- Multimedia Data Mining and Knowledge Discovery
Extra resources for Advanced Data Mining and Applications: 10th International Conference, ADMA 2014, Guilin, China, December 19-21, 2014. Proceedings
X. Yu, and Z. ): ADMA 2014, LNAI 8933, pp. 16–29, 2014. c Springer International Publishing Switzerland 2014 FHN: Eﬃcient Mining of High-Utility Itemsets with Negative Unit Proﬁts 17 has also inspired several important data mining tasks such as high-utility sequential pattern mining [15,16], high-utility episode mining  and high-utility stream mining . The problem of HUIM is widely recognized as more diﬃcult than the problem of FIM. In FIM, the downward-closure property states that the support of an itemset is anti-monotonic, that is the supersets of an infrequent itemset are infrequent and subsets of a frequent itemset are frequent.
G. proprietary printer cartridges). It was demonstrated that if classical HUIM algorithms are applied on databases containing items with negative unit proﬁts, they can generate an incomplete set of HUIs . The reason is that these algorithms over-estimate the utility of itemsets to prune the search space. But, when items with negative unit proﬁts are considered, these estimations may become underestimations, and thus HUIs may be pruned. The state-of-the-art algorithm for mining HUIs while considering negative unit proﬁts is HUINIV-Mine .
Data Eng. 21(12), 1708–1721 (2009) 4. : FHM: Faster High-Utility Itemset Mining using Estimated Utility Co-occurrence Pruning. W. ) ISMIS 2014. LNCS, vol. 8502, pp. 83–92. Springer, Heidelberg (2014) 5. : Fast vertical mining of sequential patterns using co-occurrence information. -Y. ) PAKDD 2014, Part I. LNCS, vol. 8443, pp. 40–52. Springer, Heidelberg (2014) 6. : VMSP: Eﬃcient Vertical Mining of Maximal Sequential Patterns. , van Beek, P. ) Canadian AI. LNCS, vol. 8436, pp. 83–94. Springer, Heidelberg (2014) 7.
Advanced Data Mining and Applications: 10th International Conference, ADMA 2014, Guilin, China, December 19-21, 2014. Proceedings by Xudong Luo, Jeffrey Xu Yu, Zhi Li