By Fabrice Guillet, Bruno Pinaud, Gilles Venturini
This e-book provides a set of consultant and novel paintings within the box of knowledge mining, wisdom discovery, clustering and class, in response to multiplied and transformed types of a variety of the simplest papers initially offered in French on the EGC 2014 and EGC 2015 meetings held in Rennes (France) in January 2014 and Luxembourg in January 2015. The e-book is in 3 components: the 1st 4 chapters speak about optimization concerns in information mining. the second one half explores particular caliber measures, dissimilarities and ultrametrics. the ultimate chapters concentrate on semantics, ontologies and social networks.
Written for PhD and MSc scholars, in addition to researchers operating within the box, it addresses either theoretical and useful facets of information discovery and management.
Read or Download Advances in Knowledge Discovery and Management: Volume 6 PDF
Similar data mining books
Data Mining in Agriculture represents a finished attempt to supply graduate scholars and researchers with an analytical textual content on information mining thoughts utilized to agriculture and environmental comparable fields. This ebook offers either theoretical and functional insights with a spotlight on providing the context of every information mining approach relatively intuitively with plentiful concrete examples represented graphically and with algorithms written in MATLAB®.
This booklet includes priceless reviews in information mining from either foundational and functional views. The foundational reviews of information mining may also help to put an outstanding beginning for info mining as a systematic self-discipline, whereas the sensible reviews of knowledge mining could lead to new info mining paradigms and algorithms.
This ebook constitutes the refereed lawsuits of the seventeenth foreign convention on information Warehousing and data Discovery, DaWaK 2015, held in Valencia, Spain, September 2015. The 31 revised complete papers offered have been conscientiously reviewed and chosen from ninety submissions. The papers are geared up in topical sections similarity degree and clustering; facts mining; social computing; heterogeneos networks and information; info warehouses; circulate processing; functions of massive information research; and large facts.
This ebook is dedicated to the modeling and knowing of advanced city structures. This moment quantity of knowing complicated city platforms makes a speciality of the demanding situations of the modeling instruments, referring to, e. g. , the standard and volume of information and the choice of an acceptable modeling technique. it truly is intended to help city decision-makers—including municipal politicians, spatial planners, and citizen groups—in opting for a suitable modeling technique for his or her specific modeling specifications.
- Big Data Analytics: Third International Conference, BDA 2014, New Delhi, India, December 20-23, 2014. Proceedings
- Data Mining Techniques in CRM: Inside Customer Segmentation
- Data-Driven Process Discovery and Analysis: 4th International Symposium, SIMPDA 2014, Milan, Italy, November 19-21, 2014, Revised Selected Papers
- Social Sensing: Building Reliable Systems on Unreliable Data
- Data Mining for Genomics and Proteomics: Analysis of Gene and Protein Expression Data (Wiley Series on Methods and Applications in Data Mining)
Additional info for Advances in Knowledge Discovery and Management: Volume 6
Efficient sort-based skyline evaluation. ACM Transactions on Database Systems, 33(4), 1–49. Bøgh, K. , & Magnani, M. (2013). Efficient GPU-based skyline computation. In Proceedings of the Ninth International Workshop on Data Management on New Hardware, DaMoN 2013 (pp. 5:1–5:6). New York: ACM. , & Stocker, K. (2001). The skyline operator. In Proceedings of ICDE 2001 (pp. 421–430). , & Zhang, Z. (2006a). Finding k-dominant skylines in high dimensional space. In Proceedings of SIGMOD 2006 (pp. 503–514).
1. Experiments on substantially larger datasets are necessary to evaluate the performance of our approach on real data streams and will be the subject of future work. Furthermore, we will also consider the possibility of solving our optimization problem in two steps : a first convex optimization step using convex approximation of the complete criterion and a second non convex optimization step that could be solved by the method of Composite Minimization (Nesterov 2013). , & Moulines, E. (2013).
Selecting stars: The k most representative skyline operator. In Proceedings of the ICDE 2007 (pp. 86–95). 38 H. Jaudoin et al. , & He, X. (2011). A survey of outlier detection methodologies and their applications. In Proceedings of Third International Conference Artificial Intelligence and Computational Intelligence, Part I, AICI 2011, Taiyuan, China, September 24–25, 2011 (pp. 380–387). , & Smith, E. (1997). On typicality and vagueness. Cognition, 64, 189–206. , & Seeger, B. (2005). Progressive skyline computation in database systems.