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Combining Knowledge Discovery and Knowledge Engineering to Build IDSs

Wenke Lee, Salvatore J. Stolfo
1999 International Symposium on Recent Advances in Intrusion Detection  
We have been developing a data mining (i.e., knowledge discovery) framework, MADAM ID, for Mining Audit Data for Automated Models for Intrusion Detection [LSM98, LSM99b, LSM99a] .  ...  A critical requirement for the classification rules to be effective is that an appropriate set of features need to be first constructed and included in the audit records.  ...  ) definitions for data mining tasks.  ... 
dblp:conf/raid/LeeS99 fatcat:ulpn5imxxvewfhqhfejkrlcsyq

Data Mining and Its Applications for Knowledge Management : A Literature Review from 2007 to 2012

Tipawan Silwattananusarn
2012 International Journal of Data Mining & Knowledge Management Process  
The discussion on the findings is divided into 4 topics: (i) knowledge resource; (ii) knowledge types and/or knowledge datasets; (iii) data mining tasks; and (iv) data mining techniques and applications  ...  The article first briefly describes the definition of data mining and data mining functionality.  ...  Data mining techniques can mine and construct group-based knowledge flows (GKFs) prototype for task-based groups [16] . 8.  ... 
doi:10.5121/ijdkp.2012.2502 fatcat:o646jmu3erayxklidxblpmmwea

Extraction of Principle Knowledge from Process Patents for Manufacturing Process Innovation

Gangfeng Wang, Xitian Tian, Junhao Geng, Richard Evans, Shengchuang Che
2016 Procedia CIRP  
and technology abstraction of TRIZ (the theory of inventive problem solving); and (3) constructing a domain process contradiction matrix and mapping the relationship between the matrix and the corresponding  ...  Process patents contain substantial knowledge of the principles behind manufacturing process problems-solving; however, this knowledge is implicit in lengthy texts and cannot be directly reused in innovation  ...  Thus construction process mainly consists of the following parts: process patents classification, process contradiction parameters mining, contradiction solving principles mining and principle knowledge  ... 
doi:10.1016/j.procir.2016.10.053 fatcat:2iszye2u5vg2vejbvseolodgwu

An Efficient Mining for Recommendation System for Academics

2020 International journal of recent technology and engineering  
A Bayesian network is applied to construct a verisimilitude model which would quotation the pertinent tidings from the knowledge tree to construct the recommendation and word would be scored through TF-IDF  ...  for research article based on researcher choice.  ...  Base Retrieved Research Paper For Data Mining, Precision = 34/ (34+2) = 0.9444 2.  ... 
doi:10.35940/ijrte.e5924.018520 fatcat:3gv3nbs57vfvhpb7dew7j7vifa

The Research and Implementation of Data Mining Component Library System

Peng Peng, Qianli Ma, Chaoxiong Li
2009 2009 WRI World Congress on Software Engineering  
Abstract:With the wide application of business intelligence in corporate, the demand for data mining software increases daily.  ...  of data mining.  ...  Implementation of component model Component classification based on data mining function According to the abstraction and summary of the data mining business, the entire data mining business can be divided  ... 
doi:10.1109/wcse.2009.260 fatcat:kx2pbjjjobb2fody5u7nghcskm

Data mining in manufacturing: a review based on the kind of knowledge

A. K. Choudhary, J. A. Harding, M. K. Tiwari
2008 Journal of Intelligent Manufacturing  
Data mining has emerged as an important tool for knowledge acquisition in manufacturing databases.  ...  A novel text mining approach has also been applied to the abstracts and keywords of 150 identified literatures to identify the research gaps and find the linkages between knowledge area, knowledge type  ...  The generated knowledge can be applied to construct a model for selection of subassemblies for timely delivery from the suppliers to the contractors.  ... 
doi:10.1007/s10845-008-0145-x fatcat:rt4aytttffhe3fl7memlodiysa

Real-Time Knowledge Discovery and Dissemination for Intelligence Analysis

Bhavani M. Thuraisingham, Latifur Khan, Murat Kantarcioglu, Sonia Chib, Jiawei Han, Sang Hyuk Son
2009 2009 42nd Hawaii International Conference on System Sciences  
This paper describes the issues and challenges for real-time knowledge discovery and then discusses approaches and challenges for real-time data mining and stream mining.  ...  levels of abstraction and with appropriate dimension combinations.  ...  For all of these applications there is an urgent need to mine the data and extract knowledge in real-time. Therefore, we need tools and techniques for real-time data mining.  ... 
doi:10.1109/hicss.2009.363 dblp:conf/hicss/ThuraisinghamKKCHS09 fatcat:euta372kxnfwngtpaf6gthsub4

Automatic ontology generation for data mining using fca and clustering [article]

Amel Grissa Touzi, Hela Ben Massoud, Alaya Ayadi
2013 arXiv   pre-print
in this paper a new approach for automatic generation of Fuzzy Ontology of Data Mining (FODM), through the fusion of conceptual clustering, fuzzy logic, and FCA.  ...  Motivated by the increased need for formalized representations of the domain of Data Mining, the success of using Formal Concept Analysis (FCA) and Ontology in several Computer Science fields, we present  ...  Many researchers in the field of data mining have tried to construct ontology for data mining targeted to solve some specific problems.  ... 
arXiv:1311.1764v1 fatcat:yclww7hsyjbqpc2igew252gogi

Data Mining Task Tools Techniques and Applications
IJARCCE - Computer and Communication Engineering

2014 IJARCCE  
Data mining tools predict future trends and behaviours, allowing business to make proactive and present knowledge in the form which is easily understood to human.  ...  It helps in classifying, segmenting data and in hypothesis formation. With such a vast amount of data, there is need for powerful technique for better interpretation of these data.  ...  Figure 1 : 1 Figure 1: A typical Knowledge Discovery process II. DATA MINING TASK A. Summarization Summarization is the generalization or abstraction of data.  ... 
doi:10.17148/ijarcce.2014.31003 fatcat:frbqpgkdhzhf5gnbk3g2fnrumm

A Conceptual Framework of Data Mining [chapter]

Yiyu Yao, Ning Zhong, Yan Zhao
2008 Studies in Computational Intelligence  
The layered framework is demonstrated by applying it to three sub-fields of data mining, classification, measurements, and explanation-oriented data mining.  ...  It is evident that the conceptual studies of data mining as a scientific research field, instead of a collection of isolated algorithms, are needed for a further development of the field.  ...  , have been proposed and studied for knowledge extraction and abstraction.  ... 
doi:10.1007/978-3-540-78488-3_29 fatcat:x3s2gu3pjja33bg7wycrwwamxy

Gained Knowledge Exchange and Analysis for Meta-Learning

Norbert Jankowski, Krzysztof Grabczewski
2007 2007 International Conference on Machine Learning and Cybernetics  
Implemented in a general data mining framework, it provides tools for sophisticated analysis of adaptive processes of heterogeneous machines.  ...  We propose a methodology for information exchange between machines of different abstraction levels. Inter-machine communication is based on uniform representation of gained knowledge.  ...  It can be successfully used for miscellaneous, sophisticated applications in data mining including construction of different types of classification committees and other ensembles of machines, feature  ... 
doi:10.1109/icmlc.2007.4370251 fatcat:2drg4bxrgfbrxopnw7qm77buje

Automated Software Design Reusability using a Unique Machine Learning Technique

The proposed model is validated through a numerical analysis that shows the effectiveness of the system in terms of both classification accuracy and computational efficiency.  ...  Further, the trend of research evolved towards the mining of software engineering data, which means the approaches are mostly intended to perform knowledge discovery from the data itself.  ...  Research Gap Analysis From the critical review of the existing trend of research draws the attention in many aspects such as-Even though data mining for knowledge discovery is applied in software engineering  ... 
doi:10.35940/ijitee.e3010.039520 fatcat:aqjibljxijhcbffbx5ijzh75me

Multi-level temporal abstraction for medical scenario construction

Anne-Sophie Silvent, Michel Dojat, Catherine Garbay
2005 International Journal of Adaptive Control and Signal Processing  
In this paper, we present a methodology for data abstraction and for the extraction of specific events (data mining) to eventually construct such scenarios.  ...  Data abstraction and data mining are based on the management of three key concepts, data, information and knowledge, which are instantiated via an ontology specific of our medical domain application.  ...  abstraction and data mining in knowledge discovery.  ... 
doi:10.1002/acs.855 fatcat:4zh27t2xb5aqxnnwn6nk2vadsa

Experience Management with Task-Configurations and Task-Patterns for Descriptive Data Mining

Martin Atzmüller
2007 Deutsche Jahrestagung für Künstliche Intelligenz  
Determining and instantiating an appropriate data mining task and method is often rather difficult, especially for inexperienced users.  ...  in descriptive data mining.  ...  ., classification, clustering, description) and method selection in data mining and knowledge discovery are the critical steps for successfully solving the data mining problem at hand.  ... 
dblp:conf/ki/Atzmuller07 fatcat:rmznd6tui5ccfkcyum43jm7rpi

Survey of Data Mining Techniques used in Healthcare Domain

Sheenal Patel, Hardik Patel
2016 International Journal of Information Sciences and Techniques  
In last decade, there has been increase in usage of data mining techniques on medical data for determining useful trends or patterns that are used in analysis and decision making.  ...  This paper features various Data Mining techniques such as classification, clustering, association and also highlights related work to analyse and predict human disease.  ...  DATA MINING TECHNIQUES Data mining techniques such as association, classification and clustering are used by healthcare organization to increase their capability for building appropriate conclusions regarding  ... 
doi:10.5121/ijist.2016.6206 fatcat:obbnbm7mrbed7ikqxbe2uqe4yy
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