difference between data information and knowledge ppt

... statistics, ma- chine learning, and data visualization. Data mining has emerged as a direct outcome of the data explosion that resulted from the success in database and data warehous- ing technologies ... of such streams of data and their characteristics are: • a pair of Landsat 7 and Terra spacecraft generates 350 GB of data per day in NASA Earth Observation System EOS (Park and Kargupta, 2002); ... NetFlow data (Coughlan, 2004). The widespread dissemination and rapid increase of data stream generators cou- pled with high demand to utilize these streams of data in critical real-time data analysis

Ngày tải lên: 04/07/2014, 05:21

... dimensional data is partitioned into sequential chunks based on their arrival time. Let S i be the data that came in between time t i and t i+1 . Figure 40.1 shows the distri- bution of the data and ... if c ∈{0, 1} and the class distribution is uniform, we have MSE r = .25. Since a random model does not contain useful knowledge about the data, we use MSE r , the error rate of the random classifier ... overfitting and conflicting concepts. We should not discard data that may still provide useful information to classify the current test examples. Figure 40.2(c) shows that the combination of S 2 and S

Ngày tải lên: 04/07/2014, 05:21

... requirements and estimation of risk is performed. In the data understanding phase data collected and char- acterized. Data quality is also assessed. During data preparation, tables, records and attributes ... attempt to standardise the process of Data Mining. In CRISP-DM, six interrelated phases are used to describe the Data Mining process: business understanding, data understanding, data prepa- ration, ... timely manner. 6. Security. Data and information about the Data Mining problem may contain sensitive information and must not to be revealed outside the project. Access to information must be controlled.

Ngày tải lên: 04/07/2014, 06:20

... knowledge and data stored in medical databases require the development of specialized tools for accessing the data, data analysis, knowledge discovery, and effective use of stored knowledge and ... amounts of data stored in medical databases require the development of specialized tools for accessing the data, data analysis, knowledge discovery, and effective use of stored knowledge and data. ... of standards in terminology, vocabularies and formats to support multi- linguality and sharing of data, • standards for the abstraction and visualization of data, • standards for interfaces between

Ngày tải lên: 04/07/2014, 06:20

... however, in the areas where data is accompanied with knowledge bases, and where data repositories storing heterogenous data from different sources took ground. 58 Data Mining in Medicine 1129 ... (attribute) A i and the difference between attribute values is defined as follows difference( x i ,y i )= ⎧ ⎪ ⎪ ⎪ ⎨ ⎪ ⎪ ⎪ ⎩ |x i −y i | if A i is continuous 0ifA i is discrete and x i = y i 1 otherwise ... input, a hidden and and output layer of nodes is given in Figure 58.3.b. The number of nodes in the input and output layers is domain-dependent and, respectively, is related to number and type of

Ngày tải lên: 04/07/2014, 06:20

... for documents (e.g., unstructured data) , metadata (semi structured to structured data, mostly in XML) and extracted information (mostly struc- tured, tabular data) . NHECD assumes that all target ... implemented on Drupal, which stores and manages the entire frontend database (including user information and usage patterns). 2. The user interface component that handles all the input or requests ... possible to perform data mining on the results. Data mining will result in validated results and further knowledge discovery. This part of NHECD results is targeted at Nanotox scientists and regulators.

Ngày tải lên: 04/07/2014, 06:20

... Apostolou, Andreas Abecker and Ron Young Knowledge Asset Management 1-85233-583-1 Michalis Vazirgiannis, Maria Halkidi and Dimitrios Gunopulos Uncertainty Handling and Quality Assessment in Data Mining ... Tan, E.F.Khor and T.H Lee Multiobjective Evolutionary Algorithms and Applications 1-85233-836-9 Nikhil R Pal and Lakhmi Jain (Eds) Advanced Techniques in Knowledge Discovery and Data Mining 1-85233-867-9 ... Papadopoulos and Yannis Theodoridis R-trees: Theory and Applications 1-85233-977-2 Sanghamitra Bandyopadhyay, Ujjwal Maulik, Lawrence B Holder and Diane J Cook (Eds) Advanced Methods for Knowledge

Ngày tải lên: 07/09/2020, 13:19

... Union, Inc. and Visa U.S.A.; credit reporting agencies, such as Equifax Information Services LLC, Experian Information Solutions, Inc., and Trans Union LLC.; and information management and destruction ... for the information destruction industry) and the Coalition to Implement the FACT Act (representing trade associations and companies that furnish, use, collect, and disclose consumer information) . 10 These ... example, expanding the scope of information covered under the Rule to include payroll records and credit card receipts 13 or all information stored in the same file as consumer report information. 14 The

Ngày tải lên: 15/03/2014, 07:20

... birth, and before discharge) and clinical, imaging and electrophysiological predictors, and neurological... unexplained 4 Brain Damage – Bridging Between Basic Research and ... risk factor for developing stroke and vascular dementia. Chapter 5 reviews the current understanding of the etiology and pathogenesis of Alzheimer´s Disease (AD) and Parkinson´s Disease (PD), with ... [...]... require follow up and management of their handicaps: regimens to do this have been 16 Brain Damage – Bridging Between Basic Research and Clinics described (Robertson

Ngày tải lên: 28/06/2014, 12:20

... clustering, association rule mining, and attribute selection. Getting to know the data is is a very important part of Data Mining, and many data visualization facilities and data preprocessing tools are ... 1043, 1181, 1189 Data cleaning, 19, 615 Data collection, 1084 Data envelop analysis (DEA), 968 Data management, 559 Data mining, 10 82 Data Mining Tools, 1155 Data reduction, ... vectors, computing random projections, and processing time series data. Unsupervised instance filters transform sparse instances into non-sparse instances and vice versa, randomize and resample sets

Ngày tải lên: 04/07/2014, 05:21

... tools and techniques, Morgan Kaufmann Pub, 2005. Wu, X. and Kumar, V. and Ross Quinlan, J. and Ghosh, J. and Yang, Q. and Motoda, H. and McLachlan, G.J. and Ng, A. and Liu, B. and Yu, P.S. and ... Data Mining and Knowledge Discovery, 15(1):87-97, 2007. Larose, D.T., Discovering knowledge in data: an introduction to data mining, John Wiley and Sons, 2005. Maimon O., and Rokach, L. Data Mining ... algorithms in data mining, Knowledge and Information Systems, 14(1): 1–37, 2008. Part I Preprocessing Methods 2 Data Cleansing: A Prelude to Knowledge Discovery Jonathan I. Maletic 1 and Andrian

Ngày tải lên: 04/07/2014, 05:21

... 0ifx i = y i , 1ifx and y are symbolic and x i = y i , or x i =?ory i =?, |x i −y i | r if x i and y i are numbers and x i = y i , where r is the difference between the maximum and minimum of the ... Latkowski and Mikolajczyk, 2004). In this method a data set is decomposed into complete data subsets, rule sets are induced from such data subsets, and finally these rule sets are merged. 3 Handling ... other methods to handle missing attribute values. One of them is event-covering method (Chiu and Wong, 1986), (Wong and Chiu, 1987), based on an interdependency between known and missing attribute

Ngày tải lên: 04/07/2014, 05:21

... right hand side where d m and d > r, and ap- proximate the eigenvector of the full kernel matrix K mm by evaluating the left hand rows (and hence columns) are linearly independent, and suppose ... video data) and to make the features more robust. The above features, computed by taking projections along the n’s, are first translated and normalized so that the signal data has zero mean and ... behavioral sciences (Borg and Groenen, 1997). MDS starts with a measure of dissimilarity between each pair of data points in the dataset (note that this measure can be very general, and in particular

Ngày tải lên: 04/07/2014, 05:21

... 2005b, pp 131–158. Rokach, L. and Maimon, O., Clustering methods, Data Mining and Knowledge Discovery Handbook, pp. 321–352, 2005, Springer. Rokach, L. and Maimon, O., Data mining for improving the ... quantitative data into qualitative data. Data Mining applications often involve quantitative data. However, there exist many learning algorithms that are primarily oriented to handle qualitative data ... Summary. Data- mining applications often involve quantitative data. However, learning from quantitative data is often less effective and less efficient than learning from qualitative data. Discretization

Ngày tải lên: 04/07/2014, 05:21

... analysis, and other data- mining tasks (Hawkins, 1980, Barnett and Lewis, 1994, Ruts and Rousseeuw, 1996, Fawcett and Provost, 1997, Johnson et al., 1998, Penny and Jolliffe, 2001,Acuna and Rodriguez, ... Rousseeuw, 1990, Ng and Han, 1994, Ramaswamy et al., 2000, Barbara and Chen, 2000, Shekhar and Chawla, 2002, Shekhar and Lu, 2001, Shekhar and Lu, 2002, Acuna and Rodriguez, 2004). Hu and Sung (2003) ... quantitative data flourish, and the learning algorithms many of which are more adept at learning from qualitative data. Hence, discretization has an important role in Data Mining and knowledge discovery.

Ngày tải lên: 04/07/2014, 05:21

... When data is limited, it is common practice to re-sample the data, that is, partition the data into training and test sets in different ways. An inducer is trained and tested for each partition and ... is provided. Random sub-sampling and n-fold cross-validation are two common methods of re-sampling. In random subsampling, the data is randomly partitioned into disjoint training and test sets ... trade-off between the training error and the confidence assigned to the training error as a predictor for the generalization error, measured by the difference between the generalization and training

Ngày tải lên: 04/07/2014, 05:21

... Multimedia Data Mining 58 Data Mining in Medicine Nada Lavra ˇ c, Bla ˇ z Zupan 1111 59 Learning Information Patterns in Biological Databases - Stochastic Data Mining Gautam B. Singh 1137 60 Data Mining ... Rokach 959 51 Data Mining using Decomposition Methods Lior Rokach, Oded Maimon 981 52 Information Fusion - Methods and Aggregation Operators Vicenc¸ Torra 999 53 Parallel And Grid-Based Data Mining ... 759 40 Mining Concept-Drifting Data Streams Haixun Wang, Philip S. Yu, Jiawei Han 789 41 Mining High-Dimensional Data Wei Wang, Jiong Yang 803 42 Text Mining and Information Extraction Moty Ben-Dov,...

Ngày tải lên: 04/07/2014, 05:21

... understanding phenomena from the data, analysis and prediction. The accessibility and abundance of data today makes Knowledge Discovery and Data Mining a matter of considerable importance and necessity. ... Process of Knowledge Discovery in Databases. be determined. This includes finding out what data is available, obtaining additional necessary data, and then integrating all the data for the knowledge discovery ... the interactive and iterative aspect of the KDD is taking place. It starts with the best available data set and later expands and observes the effect in terms of knowledge discovery and modeling. 3....

Ngày tải lên: 04/07/2014, 05:21

... analyze, and investigate such very large data sets has given rise to the fields of Data Mining (DM) and data warehousing (DW). Without clean and correct data the usefulness of Data Mining and data ... examining databases, detecting missing and incorrect data, and correcting errors. Other recent work relating to data cleansing includes (Bochicchio and Longo, 2003, Li and Fang, 1989). Data Mining ... areas that include data cleansing as part of their defining processes are: data warehousing, knowledge discovery in databases, and data/ information quality management (e.g., Total Data Quality Management...

Ngày tải lên: 04/07/2014, 05:21

... (Silva and Tenenbaum, 2002). Landmark Isomap simply employs land- mark MDS (Silva and Tenenbaum, 2002) to addresses this problem, computing all distances as geodesic distances to the landmarks. ... clustering and Laplacian eigen- maps are local (for example, LLE attempts to preserve local translations, rotations and scalings of the data) . Landmark Isomap is still global in this sense, but the land- mark ... Let’s start by defining a simple mapping from a dataset to an undirected graph G by forming a one-to-one correspondence between nodes in the graph and data points. If two nodes i, j are connected...

Ngày tải lên: 04/07/2014, 05:21