data mining research papers 2012-110

 Data Mining Techniques: A Tool For Knowledge Management System In Agriculture
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L Sharma, N Mehta ,
Abstract: Agriculture data is highly diversified in terms of nature, interdependencies and
resources. For balanced and sustainable development of agriculture these resources need
to be evaluated, monitored and analyzed so that proper policy implication could be drawn. 

 Research on Privacy Preserving Data Mining Pingshui Wang1, 2, Jiandong Wang1, Xinfeng Zhu1, Jian Jiang
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P Wang, J Wang, X Zhu
Abstract. In recent years, with the explosive development in Internet, data storage and data
processing technologies, privacy preservation has been one of the greater concerns in data
mining. A number of methods and techniques have been developed for privacy preserving 

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M Dobrota, Z Radojicic, M Dobrota ,BUSINESS INTELLIGENCE AND ,
Abstract: This paper discusses the prediction of customer satisfaction with mobile operating
systems (OS) using the classification and regression trees (CART) method. This reliable and
effective decision-making technique provides high prediction accuracy with a simple 

 State-of-art in Statistical Anonymization Techniques for Privacy Preserving Data Mining
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Abstract-With the increased and vast use of online data, security in data mining has now
become very important. Anonymity techniques have proved very useful in distributed
computation. More techniques are still under research and improvements for achieving 

 Agent-Based Data Mining In Mobile Commerce: An Overview
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J Nithya, R Geetha ,
Abstract-Data mining technology has emerged as a means for identifying patterns and
trends from large quantities of data. The Data Mining technology normally adopts data
integration method to generate Data warehouse, on which to gather all data into a central 

 Mining RCS Data
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CSSMR Vedala, TS Reddy ,
Page 1. Mining RCS Data  Abstract ,As software systems evolve, it becomes important to know
and to track the evolution of a system and its components. Data mining tools helps us to find the
relationships between these components from patterns in the attributes of the data. 

 Statistical Methods and Optimization in Data Mining
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E Macedo, A Freitas ,
The increasing number of the sequenced genomes has created new challenges in several
scientific domains, namely statistics, optimization and Modern heuristic techniques for combinatorial problems. Advanced topics in computer science
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Decision Tree and Ensemble Learning Based on Ant Colony Optimization Google Books Result Modern heuristic techniques for combinatorial problems . Faculty library sciences Series: Advanced topics in computer science series; Alternative call (PDF) Modern Heuristic Search Methods

Software Agents Michael R. Genesereth Logic Group Computer Science Department Stanford University
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The software world is one of great richness and diversity. Many thousands of software products are available to users today, providing a wide variety of information and services in a wide variety of domains. While most of these programs provide their users with significant Classical complexity theory analyzes and classifies problems by the amount of a resource, usually time or space, that is required by algorithms solving them. It was a fundamental idea, going back to the work of Hartmanis and Stearns in the early 1960s, to measure the required

The combinatorics of network reliability, International Series of Monographs on Computer Science
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This book develops combinatorial tools which are useful for reliability analysis, as demonstrated with a probabilistic network model. Basic results in combinatorial enumeration are reviewed, along with classical theorems on connectivity and cutsets. More developed

Languages and machines: an introduction to the theory of computer science
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Languages and machines : an introduction to the theory of computer . Theory of Computing 2015/2016 (FUB MSc in Computer Science ) Languages and Machines, which is intended for computer scientists in the theoretical foundations of their subject, gives a mathematically sound In the late 1960s and early 1970s, the concepts of graph transformation and graph grammars started to become of interest in picture processing and computer science . The main idea was to generalize well-known rewriting techniques from strings and trees to Parsing is the process of structuring a linear representation in accordance with a given grammar. This definition has been kept abstract on purpose to allow as wide an interpretation as possible. The linear representation may be a sentence, a computer

The Cambridge distributed computing system. International computer science series
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The Development of Component-based Information Systems Google Books Result The Cambridge Distributed Computing System is an early discontinued distributed operating system, . (International computer science series) Bibliography: p. The 100 Best Computer Science Programs in the

Logic and the challenge of computer science
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Nowadays computer science is surpassing mathematics as the primary field of logic applications, but logic is not tuned properly to the new role. In particular, classical logic is preoccupied mostly with infinite static structures whereas many objects of interest in

Computer science unplugged
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For kids ages 7 to 14: This educational 50 minute show is an action-packed, zany time exploring neat ideas in computer science . It has been performed for over 20 years in classrooms, science museums, science festivals, and at educational events. Kids, and the

The Profession of IT, Is Computer Science Science
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COMMUNICATIONS OF THE ACM draw on the same fundamental principles. In 1989, we used the term computing instead of computer science , mathematics, and engineering. Today, computing science, engineering, mathematics, art

Discrete mathematical structures with applications to computer science
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The objectives of the course are: To develop Professional Skills through effective communication To introduce a number of Mathematical Foundation to be serving as tools even today in the development of theoretical computer science To gain some confidence on

Bringing computational thinking to K-12: what is Involved and what is the role of the computer science education community
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When Jeanette Wing [13] launched a discussion regarding the role of computational thinking across all disciplines, she ignited a profound engagement with the core questions of what computer science is and what it might contribute to solving problems across the

Modern DC-to-DC Switchmode Power Converter Circuits (Van Nostrand Reinhold Electrical/ Computer Science and Engineering Series)
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As each area of technology with a potential for significantly impacting any major segment of the electronics industry evolves, it often is accompanied by the development of a succession of new circuits. Each new circuit indeed appears different, employing different components

Information technology research: A practical guide for computer science and informatics
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Information Technology Research: A Practical Guide for Computer

Scientific methods in computer science
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ABSTRACT This paper analyzes scientific aspects of Computer Science . First it defines science and scientific method in

Active learning and its use in computer science
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Student learning and the depth of the students knowledge increase when active learning methods are employed in the classroom. Active learning strategies are discussed in general computer science course work and as used in a theory of computation course. Difficulties

Why the high attrition rate for computer science students: some thoughts and observations
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1. Introduction At our university, there are over four hundred declared majors in Computer Science . Each semester, however, only about fifteen to twenty students graduate in this field. The freshman courses comprise overflowing multiple sections, but the upper level courses make

Form and content in computer science
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The trouble with computer science today is an obsessive concern with form instead of content. No, that is the wrong way to begin. By any previous standard the vitality of computer science is enormous; what other intellectual area ever advanced so far in twenty years

Why women avoid computer science
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COMMUNICATIONS OF THE ACM did these numbers drop, and why more sharply for women than for men For men, the explanation is obvious. Traditional paths to wealth like law, medicine, and business are more certain, and over the
s. Various numerical
transformations related to the sequenced genomes (eg, frequency of each nucleotide, 

 Toward the Influenza Virus Data Mining from a DNA Data Bank
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NG Khoa, T Van Lang, T Van Hoai, VDV Phuong ,
Abstract—Influenza virus is one of the causes of flu in human beings as well as in animals.
Vietnam, with its tropical climate, is one of the countries located in heavily affected areas of
the influenza virus. Building a localized information system of flu viruses for Vietnam 

 Development of Power System Test Bed for Data Mining of Synchrophasors Data, Cyber-Attack and Relay Testing in RTDS
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U Adhikari, TH Morris, N Dahal, S Pan, RL King ,
Abstract This paper describes the development of a hardware-in-the-loop Real Time Digital
Simulator (RTDS) enabled power system test bed used to support various types of research.
Lack of access to actual utility synchrophasors data at the university level hinders studies 

 Large Scale Remote Sensing Data Mining for Biomass Monitoring: Recent Advances and Future Challenges
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Recent advances in remote sensing instrumentation, and commercialization of remote
sensing technology has lead to the unprecedented growth in the acquisition and archival of
high resolution (spatial, spectral, and temporal) imagery. There is a great demand for 

 Data Stream Mining for Ubiquitous Environments
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 entire network of data sources. 3 CONCLUDING REMARKS In this talk we discussed
approaches to ubiquitous data mining were both data sources and processing
devices are distributed. Algorithms process local data and 

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J Cižovs ,
With the development of electronic management of production, trade, finance, etc., new
features of structured data storage have appeared which reflect the economic activities of an
enterprise. The analysis of the available data of the enterprise activity in the past aimed to 

 Data Mining Techniques in Pharmaceutical Industry
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N Chetwani, S Shrivastava, P Chopra ,SGI Reflections
Abstract Today IT technology is being used to help the pharmaceutical firms manage their
inventories and to develop new product and services. The implications are such that by a
simple process of merging the drug usage and cost of medicines (after completing the 

 Proposing an Improved Semantic and Syntactic Data Quality Mining Method using Clustering and Fuzzy Techniques
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HR Khosravani ,
 so far. The first approach is based on statistical methods while the second one uses
data mining techniques which caused further improvement in data quality evaluation
results through relying on knowledge extracting. Our proposed 

 Mining Frequent Itemsets over Recent Data Stream Based on Genetic Algorithm
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Z Yong, H Jun, G He ,
 coming. Mining over data streams is one of the most interesting issues of data mining
in recent years.  technology. Sliding window has been used in the network
communication, time-series data mining, data stream mining and so on. 

 Intelligent Information Retrieval in Data Mining
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RP Singh, P Yadav
Abstract: In this paper we present the methodologies and challenges of information retrieval.
We will focus on data mining, data warehousing, information retrieval, data mining ontology,
intelligent information retrieval. We will also focus on fundamental concepts behind all 

 Use of Data Mining in Banking
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KI Moin, QB Ahmed
Abstract In today? s globalization and cut throat competition the banks are struggling to gain
a competitive edge over each other. Apart from execution of business processes, the
creation of knowledge base and its utilization for the benefit of the bank is becoming a 

 Data Preprocessing in Web Usage Mining
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V Losarwar, M Joshi
 Vijayashri Losarwar, Dr. Madhuri Joshi Abstract It is well known that over 80% of the time
required to carry out any real world data mining project is usually spent on data
preprocessing. Data preprocessing lays the groundwork for data mining. 

 Spirometric Data Classification on the Basis of Statistical Data Mining
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MPD Junwale, AW Bhade, PN Chatur ,
Abstract—Respiratory disease is a medical term that encompasses pathological conditions
affecting the organs and tissues. A lungs disease affects health condition of many people.
Lungs diseases can be curable in early detection. Spirometry is valuable for diagnosing 

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S Mahalik ,
ABSTRACT Spatial data mining is the process of discovering interesting and previously
unknown, but potentially useful patterns from large spatial datasets. Extracting interesting
and useful patterns from spatial datasets is more difficult than extracting the corresponding 

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KV Rao, A Govardhan, KVC Rao
ABSTRACT Spatiotemporal data mining is an emerging area of research. Applications for
mining different kinds of spatiotemporal patterns and trends are being developed by
researchers in various domains. However, there is a need for underlying architecture 

 Domain Specific Video Data Mining Using Multicore Fp-Growth Tree
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G Khanvilkar, A Mhate ,spectrum, 2012
Abstract: Content based methods are necessary when text annotations are non-existent or
incomplete. Furthermore, content based methods can potentially improve retrieval accuracy
even when text annotations are present by giving additional insight into the media 

 A Wordification Approach to Relational Data Mining: Early Results
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Abstract. This paper describes a propositionalization technique called wordification.
Wordification is inspired by text mining and can be seen as a transformation of a relational
database into a corpus of documents. As in previous propositionalization methods, after 

 Exploration of Data mining techniques in Fraud Detection: Credit Card
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K Chaudhary, B Mallick ,
Abstract-Data mining has been increasing as one of the chief key features of many security
initiatives. Often, used as a means for detection of fraud, assessing risk as well. Data mining
involves the use of data analysis tools to discover unknown, valid patterns as well as 

 Distributed Data-Mining by Probability-Based Patterns
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M Kargar, F Gharbalchi
Abstract—In this paper a new method is suggested for distributed data-mining by the
probability patterns. These patterns use decision trees and decision graphs. The patterns
are cared to be valid, novel, useful, and understandable. Considering a set of functions, 

 MODIM: Model-Driven Data Integration for Mining
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 France Keywords : data integration, relational databases, distributed data sources,
data mining The success of a knowledge discovery process relies on expert-guided
iterative design and selection of datasets to be mined. In 

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M Bala, DB Ojha ,
ABSTRACT An innovative knowledge-based methodology for terrorist detection by using
Web traffic content as the audit information is presented. The proposed methodology learns
the typical behavior (‘profile’) of terrorists by applying a data mining algorithm to the textual 

 Benchmarking the Data Mining Algorithms with Adaptive Neuro-Fuzzy Inference System in GSM Churn Management
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Turkey has started to distribute Global Services of Mobile (GSM) 900 licences in 1998.
Turkcell and Telsim have been the first players in the GSM market and they bought licenses
respectively. In 2000, GSM 1800 licenses were bought by ARIA and AYCELL respectively. 

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