Multimedia data mining: state of the art and challenges
... tools can facilitate decision making in many situations. Data mining refers to the process of finding interesting patterns in data that are not ordinarily accessible by basic queries and associated results with the objective of using discovered patterns to improve decision making [104]. For example, ...
... tools can facilitate decision making in many situations. Data mining refers to the process of finding interesting patterns in data that are not ordinarily accessible by basic queries and associated results with the objective of using discovered patterns to improve decision making [104]. For example, ...
An Approach to Improve the Web Performance By
... prefetch web page that the user is likely to access soon, while he/she is viewing the currently displayed page. L Fan et al [2] investigate an approach to reduce web latency by prefetching between caching, proxies, and browsers. Research on predictive Web prefetching has involved the important issue ...
... prefetch web page that the user is likely to access soon, while he/she is viewing the currently displayed page. L Fan et al [2] investigate an approach to reduce web latency by prefetching between caching, proxies, and browsers. Research on predictive Web prefetching has involved the important issue ...
False Positives Reduction Techniques in Intrusion Detection
... processed (e.g., false positives classified with high confidence are discarded). In this system, a fast and effective rule learner was used that is RIPPER. It can build a set of rules discriminating between classes (i.e. false and true alerts). The number of false alerts reduced by more than 30%. Th ...
... processed (e.g., false positives classified with high confidence are discarded). In this system, a fast and effective rule learner was used that is RIPPER. It can build a set of rules discriminating between classes (i.e. false and true alerts). The number of false alerts reduced by more than 30%. Th ...
Essence of Knowledge Discovery
... overall process of non-trivial extraction of implicit, previously unknown and potentially useful knowledge from large amounts of data • Exploration & analysis, by automatic or semi-automatic means, of large quantities of data in order to discover meaningful patterns ...
... overall process of non-trivial extraction of implicit, previously unknown and potentially useful knowledge from large amounts of data • Exploration & analysis, by automatic or semi-automatic means, of large quantities of data in order to discover meaningful patterns ...
Web mining for the integration of data mining with
... Structure: Data that describe the organization of the pages. These include intrapage structure information (the layout of various HTML or XHTML tags within a given page) and inter-page structure information (the hyperlinks connecting one page to another page); Usage: Data that describe the usage of ...
... Structure: Data that describe the organization of the pages. These include intrapage structure information (the layout of various HTML or XHTML tags within a given page) and inter-page structure information (the hyperlinks connecting one page to another page); Usage: Data that describe the usage of ...
Integration of Signature based and Anomaly based Detection
... J. Song et al. [10] have proposed a new anomaly detection method by which they are able to optimize the values of two parameters, i.e., a (no. of attack data) and k (no. of normal pattern), without predefining them. Among the three parameters, they have focused on only two a and k, because they have ...
... J. Song et al. [10] have proposed a new anomaly detection method by which they are able to optimize the values of two parameters, i.e., a (no. of attack data) and k (no. of normal pattern), without predefining them. Among the three parameters, they have focused on only two a and k, because they have ...
R and Bioconductor Tools for Class Discovery Analysis: Example
... Since the major cause of most brain tumor is unidentified, it is important to study the genes that play different roles in the development of glioblastoma. Hence, gene expression profiling is essential. In addition, molecular classes which can never be the detected by looking at GBM samples under th ...
... Since the major cause of most brain tumor is unidentified, it is important to study the genes that play different roles in the development of glioblastoma. Hence, gene expression profiling is essential. In addition, molecular classes which can never be the detected by looking at GBM samples under th ...
Clustering and Mapping Web Sites for Displaying Implicit
... Web sites. The extracting method that will be exposed is founded on clustering and mapping procedures. The goal is here to extract information from hidden patterns in a large set of Web data. This goal is called Web mining. These "implicit associations" can be considered as the hidden pattern from w ...
... Web sites. The extracting method that will be exposed is founded on clustering and mapping procedures. The goal is here to extract information from hidden patterns in a large set of Web data. This goal is called Web mining. These "implicit associations" can be considered as the hidden pattern from w ...
Oracle® Data Mining Tutorial
... agreement containing restrictions on use and disclosure and are also protected by copyright, patent, and other intellectual and industrial property laws. Reverse engineering, disassembly, or decompilation of the Programs, except to the extent required to obtain interoperability with other independen ...
... agreement containing restrictions on use and disclosure and are also protected by copyright, patent, and other intellectual and industrial property laws. Reverse engineering, disassembly, or decompilation of the Programs, except to the extent required to obtain interoperability with other independen ...
A top-down approach for creating and implementing data mining
... mining process, the measurements pass through a chain of sophisticated transformations in order to acquire knowledge. Furthermore, in some applications the results are implemented as software solutions so that they can be continuously utilized. It is evident that the quality and amount of the knowle ...
... mining process, the measurements pass through a chain of sophisticated transformations in order to acquire knowledge. Furthermore, in some applications the results are implemented as software solutions so that they can be continuously utilized. It is evident that the quality and amount of the knowle ...
ADDIS ABABA UNIVERSITY
... the models. Models were built and tested by using a sample dataset of 1100 records of both alive and Died children. Several neural network and decision tree models were built and tested for their classification accuracy and many models with encouraging results were obtained. The two data mining meth ...
... the models. Models were built and tested by using a sample dataset of 1100 records of both alive and Died children. Several neural network and decision tree models were built and tested for their classification accuracy and many models with encouraging results were obtained. The two data mining meth ...
Development and Application of Data Mining Methods in Medical
... medicine. When applying data mining in medicine, additional problems such as varied information representation formats, semantic interoperability and patient privacy have to be resolved. The object of the dissertation research is the process and methods of data mining in medicine. The following topi ...
... medicine. When applying data mining in medicine, additional problems such as varied information representation formats, semantic interoperability and patient privacy have to be resolved. The object of the dissertation research is the process and methods of data mining in medicine. The following topi ...
Data Mining Tutorial
... Extraction of information is not the only process we need to perform; data mining also involves other processes such as Data Cleaning, Data Integration, Data Transformation, Data Mining, Pattern Evaluation and Data Presentation. Once all these processes are over, we would be able to use this informa ...
... Extraction of information is not the only process we need to perform; data mining also involves other processes such as Data Cleaning, Data Integration, Data Transformation, Data Mining, Pattern Evaluation and Data Presentation. Once all these processes are over, we would be able to use this informa ...
Package `subspace`
... because they are not likely to contain important information for the clustering. In the second phase, these base clusters are merged to produce subspace cluster approximations. This is achieved by computing the k-most-similar clusters for each base-cluster. Then the set of best-merge-candidates for ...
... because they are not likely to contain important information for the clustering. In the second phase, these base clusters are merged to produce subspace cluster approximations. This is achieved by computing the k-most-similar clusters for each base-cluster. Then the set of best-merge-candidates for ...
For Peer Review - Soft Computing and Intelligent Information Systems
... - Objective. The objective of data mining in each application area is different. For example, in business the main objective is to increase profit, which is tangible and can be measured in term of amounts of money, number of customers and customer loyalty. But EDM has both applied research objective ...
... - Objective. The objective of data mining in each application area is different. For example, in business the main objective is to increase profit, which is tangible and can be measured in term of amounts of money, number of customers and customer loyalty. But EDM has both applied research objective ...
lecture1422914558
... One of the attractions of data mining is that it makes it possible to analyse very large data sets in a reasonable time scale. Data mining is also suitable for complex problems involving relatively small amounts of data but where there are many fields or variables to analyse. However, for small, rel ...
... One of the attractions of data mining is that it makes it possible to analyse very large data sets in a reasonable time scale. Data mining is also suitable for complex problems involving relatively small amounts of data but where there are many fields or variables to analyse. However, for small, rel ...
PPT - Snowmass 2001
... NDMA Data Mining Challenges Fuzzy matching for records feature matching in images clustering - outcomes, other variables outlier search in many dimensions computer assisted diagnosis ...
... NDMA Data Mining Challenges Fuzzy matching for records feature matching in images clustering - outcomes, other variables outlier search in many dimensions computer assisted diagnosis ...
Nonlinear dimensionality reduction
High-dimensional data, meaning data that requires more than two or three dimensions to represent, can be difficult to interpret. One approach to simplification is to assume that the data of interest lie on an embedded non-linear manifold within the higher-dimensional space. If the manifold is of low enough dimension, the data can be visualised in the low-dimensional space.Below is a summary of some of the important algorithms from the history of manifold learning and nonlinear dimensionality reduction (NLDR). Many of these non-linear dimensionality reduction methods are related to the linear methods listed below. Non-linear methods can be broadly classified into two groups: those that provide a mapping (either from the high-dimensional space to the low-dimensional embedding or vice versa), and those that just give a visualisation. In the context of machine learning, mapping methods may be viewed as a preliminary feature extraction step, after which pattern recognition algorithms are applied. Typically those that just give a visualisation are based on proximity data – that is, distance measurements.