data mining techniques and algorithms

... Detection In Online Social Networks: Using data- mining Techniques and Fuzzy Logic i ii Anomaly Detection In Online Social Networks: Using data- mining Techniques and Fuzzy Logic Abstract The Online Social ... Discovery and Data Mining (pp 504-509) ACM Aggarwal, C C (2013) Outlier Analysis Springer Aggarwal, C C., & Wang, H (2010) Graph Data Management and Mining: A Survey of Algorithms and Applications ... online social networks data graph, including modelling, algorithms, labelling, and evaluation Anomaly Detection In Online Social Networks: Using data- mining Techniques and Fuzzy Logic iii In

Ngày tải lên: 07/08/2017, 15:46

... a data mining query language can be used to specify data mining tasks In particular, we examine how to define data warehouses and data marts in our SQL-based data mining query language, DMQL Data ... for time, item, and location are shared between both the sales and shipping fact tables In data warehousing, there is a distinction between a data warehouse and a data mart A data warehouse collects ... form of data cleaning, as well as data reduction In summary, real-world data tend to be dirty, incomplete, and inconsistent Data preprocessing techniques can improve the quality of the data, thereby

Ngày tải lên: 08/08/2014, 18:22

... data warehousing technology 3.3.4 Metadata Repository Metadata are data about data When used in a data warehouse, metadata are the data that define warehouse objects Figure 3.12 showed a metadata ... between the current detailed data and the lightly summarized data, and between the lightly summarized data and the highly summarized data Metadata should be stored and managed persistently (i.e., ... dimensions, hierarchies, and derived data definitions, as well as data mart locations and contents Operational metadata, which include data lineage (history of migrated data and the sequence of transformations

Ngày tải lên: 08/08/2014, 18:22

... partitioning the data (mining on each partition and then combining the results) and sampling the data (mining on a subset of the data) These variations can reduce the number of data scans required ... Cheung, Han, Ng, and Wong [CHNW96] Parallel and distributed association data mining under the Apriori framework was studied by Park, Chen, and Yu [PCY95b], Agrawal and Shafer [AS96], and Cheung, Han, ... association mining was studied in Han and Fu [HF95], and Srikant and Agrawal [SA95] In Srikant and Agrawal [SA95], such mining was studied in the context of generalized association rules, and an R-interest

Ngày tải lên: 08/08/2014, 18:22

... assuming a small data size Recent data mining research has built on such work, developing scalable classification and prediction techniques capable of handling large disk-resident data In this chapter, ... cuboids for city and item, city and year, city and sales, and the 3-D cuboid for item, year, and sales In this way, an iterative technique can be used to build higher-order data cubes from lower-order ... to the various classification and prediction methods presented Recent data mining research has contributed to the development of scalable algorithms for classification and prediction Additional contributions

Ngày tải lên: 08/08/2014, 18:22

... subsets D1 , D3 , , Dk and tested on D2 ; and so on Unlike the holdout and random subsampling methods above, here, each sample is used the same number of times for training and once for testing ... of data tuples The bootstrap method works well with small data sets 14 e is the base of natural logarithms, that is, e = 2.718 366 Chapter Classification and Prediction M1 New data sample M2 Data ... long processing times and the intricacies of complex data 7.9 Clustering High-Dimensional Data Most clustering methods are designed for clustering low-dimensional data and encounter challenges

Ngày tải lên: 08/08/2014, 18:22

... technology in molecular biology and develops algorithms and methods to manage and analyze biological data Because DNA and protein sequences are essential biological data and exist in huge volumes as ... prefix b , c , d , e , and f , respectively This can be done by constructing the b -, c -, d -, e -, and f -projected databases and mining them respectively The projected databases as well as the ... time-related sequence data, further development of efficient algorithms for mining various kinds of periodic patterns in sequence databases is desired 8.4 Mining Sequence Patterns in Biological Data Bioinformatics

Ngày tải lên: 08/08/2014, 18:22

... itemset stream mining; the Hoeffding tree, VFDT, and CVFDT algorithms for stream data classification; and the STREAM and CluStream algorithms for stream data clustering A time-series database consists ... retrieval and multidimensional indexing methods, should be integrated with data generalization and data mining techniques to achieve satisfactory results Techniques for mining such data are further ... (OLAP) in such data warehouses, and (2) develop effective and scalable methods for mining knowledge from object databases and/ or data warehouses The second task is largely covered by the mining of

Ngày tải lên: 08/08/2014, 18:22

... Applications and Trends in Data Mining Coupling data mining with database and/ or data warehouse systems: A data mining system should be coupled with a database and/ or data warehouse system, where ... standardize data mining products and to 11.2 Data Mining System Products and Research Prototypes 663 ensure the interoperability of data mining systems Recent efforts at defining and standardizing data mining ... difficulties using the data stored in database systems and handling large data sets efficiently In data mining systems that are loosely coupled with database and data warehouse systems, the data are retrieved

Ngày tải lên: 08/08/2014, 18:22

... the benefits of data mining in terms of time and money savings and the discovery of new knowledge 11.5 Trends in Data Mining The diversity of data, data mining tasks, and data mining approaches ... content mining, Weblog mining, and data mining services on the Internet will become one of the most important and flourishing subfields in data mining Distributed data mining: Traditional data mining ... issues in data mining The development of efficient and effective data mining methods and systems, the construction of interactive and integrated data mining environments, the design of data mining

Ngày tải lên: 08/08/2014, 18:22

... and lots of data with few measurement errors This data changes over time, and values are sometimes incomplete The data miner has to be particularly suspicious about bias introduced into the data ... dive into more detail into more modern techniques for building models and understanding data Many of these techniques have been adopted by statisticians and build on over a century of work in ... be more receptive to one type of message and some to another Determining Customer Value Customer value calculations are quite complex and although data mining has a role to play, customer value

Ngày tải lên: 14/08/2014, 11:21

... commercial data mining software packages The problem is that just by breaking the larger data set into many small subsets , the number of classes represented in each node tends to go down, and with ... Breiman, Jerome Friedman, Richard Olshen, and Charles Stone in 1984 The acronym stands for Classification and Regression Trees The CART algorithm grows binary trees and continues splitting as long as ... complexity and training set misclassification rate The CART algorithm identifies a set of such subtrees as candidate models These candidate subtrees are applied to the validation set and the tree

Ngày tải lên: 14/08/2014, 11:21

... of information out of a few hundred data points In data mining applications, the volumes of data are so large that statistical con­ cerns about confidence and accuracy are replaced by concerns ... is a start and stop, a decision that often depends on the type of busi­ ness and available data The second challenge is technical: finding these start and stop dates in available data may be ... failures In the world of customers, tens of thousands is the lower limit, since cus­ tomer databases often contain data on millions of customers and former customers Much of the statistical background

Ngày tải lên: 14/08/2014, 11:21

... MƠN HỌC KHAI THÁC DỮ LIỆU VÀ ỨNG DỤNG ĐỀ TÀI : KHAI THÁC ĐỒ THỊ DỰA TRÊN TÀI LIỆU : Data Mining: Concepts and Techniques, Jiawei Han TP.HCM – 12/2012 Tóm tắt nội dung đồ án Đồ thị biểu thị cho ... gom nhóm phân lớp liệu đồ thị khám phá chúng với phương pháp khai thác mẫu đồ thị Chương 9:Graph Mining 9.1 Khai thác đồ thị Đồ thị ngày trở nên quan trọng việc mơ hình hóa cấu trúc phức tạp (hợp ... lập mục video, thu hồi văn bản, phân tích Web nhu cầu phân tích liệu có cấu trúc ngày tăng graph mining trở thành nhiệm vụ quan trọng Ví Dụ: Mạng cộng tác tác giả Hình 1: Ví dụ ứng dụng đồ thị

Ngày tải lên: 12/11/2015, 13:20