data mining research papers 2012-201







DATA AND WEB MINING DATA
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set of data of interest is too expensive or time consuming. ? Sampling is used in data mining because processing the entire set of data of interest is too  Purpose: – Avoid curse of dimensionality – Reduce amount of time and memory required by data mining algorithms

DATA MINING–CURRENT STATE AND FUTURE TRENDS
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Abstract. Data mining discipline is recognized by many researchers and practitioners as very promising to support plenty business applications including marketing, sales, finance, credit scoring, customer relationship management. Undoubtedly, research and application of

Agent Based Data Mining in Wireless Sensor Networks: A Survey
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ABSTRACT Wireless Sensor Networks (WSNs) are nowadays widely used for monitoring physical phenomena of the environment. Traditional data mining algorithms cannot be applied to such distributed systems in which strict memory, power, and communication

PERFORMANCE ANALYSIS OF CLASSIFICATION DATA MINING TECHNIQUES OVER HEART DISEASE DATA BASE
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Abstract The healthcare industry collects huge amounts of healthcare data which, unfortunately, are not mined to discover hidden information for effective decision making. Discovery of hidden patterns and relationships often goes unexploited. Advanced data

Application of Data Mining Techniques to Predict Allergy Outbreaks among Elementary School Children
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ABSTRACT Objectives of this study are to determine if a relationship exists between occurrence of allergies among elementary school children and daily upper-air observations (temperature, relative humidity, dew point, mixing ratio) and daily air pollution (particulate

Determining the Existence of Quantitative Association Rule Hiding in Privacy Preserving Data Mining
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ABSTRACT Determining the association rules is a core topic of privacy preserving data mining. This paper aims at giving an overview to some of the previous researches done in this topic, evaluating the current status of the field, and envisioning possible future trends in this area

Available Protocols for Multi-party Computation in Privacy Preserving Data Mining
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ABSTRACT Privacy preservation is an important component in designing various data mining applications to seek a trade-off between mining utilities and protecting private information. Due to vast advancements in internet, computing and communication, multiparty

Innovative Study to the Graph-based Data Mining: Application of the Data Mining
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ABSTRACT Graph-based data mining represents a collection of techniques for mining the relational aspects of data represented as a graph. Two major approaches to graph based data mining are frequent sub graph mining and graph-based relational learning. This

Using Text and Data Mining Techniques to extract Stock Market Sentiment from Live News Streams
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Abstract. Analyzing stock market trends and sentiment is an interdisciplinary area of research being undertaken by many disciplines such as Finance, Computer Science, Statistics, and Economics. It has been well established that real time news plays a strong

Data Mining K-Clustering Problem
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Abstract In statistic and data mining, k-means clustering is well known for its efficiency in clustering large data sets. The aim is to group data points into clusters such that similar items are lumped together in the same cluster. In general, given a set of objects together with

Data Mining System for Selection of Best Basket Ball Team
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ABSTRACT Selection of a team for any game is a difficult task. It is totally governed by the selection committee members, which may be bias and therefore appropriate team is not selected. This may cause the failure in the NationalInternational level competitions. In

A New Data Mining Based Network Intrusion Detection Model
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ABSTRACT As information systems are more widely used in the field of internet nowadays the need for secure networks is tremendously increased. New intelligent Intrusion Detection Systems (IDSs) based on sophisticated algorithms rather than current signature base

A Hierarchical Dynamic Load Balancing Strategy for Distributed Data Mining
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Abstract Extracting useful knowledge from data sets measuring in gigabytes and even terabytes is a challenging research area for the data mining community. Sequential approaches suffer from a performance problem due to the fact that they have to mine

depth Coverage and Analysis of Information Fusion Technique (with Enhanced Algorithm for Feature Selection with Multiple Classifier System) for Data Mining
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ABSTRACT The main objective of Information Fusion techniques in Data Mining is to show that final information generated to be of superior quality and more meaningful, than the information available from the actual (primary) sources. Fusion, by definition, requires a

Mobile Sensor Data Mining
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At an ever increasing rate, the smartphones and other devices people carry with them in their everyday lives are packed with sensors and processing power. This provides an unprecedented opportunity to apply data mining techniques to people s activities as they

A Study Survey of Privacy Preserving Data Mining
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ABSTRACT Data mining is the extraction of interesting patterns or knowledge from huge amount of data. In recent years, with the explosive development in Internet, data storage and data processing technologies, privacy preservation has been one of the greater concerns

Enhancement of CURE Clustering Technique in Data Mining
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Abstract The precious information is embedded in large databases. To extract them has become an interesting area of Data mining. Clustering, in data mining, is useful for discovering groups and identifying interesting distributions in the underlying data [5].

A hybrid Evolutionary Functional Link Artificial Neural Network for Data mining and Classification
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ABSTRACT This paper presents a specific structure of neural network as the functional link artificial neural network (FLANN). This technique has been employed for classification tasks of data mining. In fact, there are a few studies that used this tool for solving classification

A Business Intelligence Framework to Provide Performance Management through a HolisticData Mining View
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Abstract Traditional views of business intelligence have mainly focused on the physical and human aspects of the organization. This paper tries to show that a new information view of business activities can make a platform for developing business intelligence and support

Data Mining Using RFM Analysis
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RFM stands for Recency, Frequency and Monetary value. RFM analysis is a marketing technique used for analyzing customer behavior such as how recently a customer has purchased (recency), how often the customer purchases (frequency), and how much the

Assessing the Learning and Transfer of Data Collection Inquiry Skills Using Educational Data Mining on Students Log Files
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ABSTRACT In this paper we explored whether engaging in two inquiry skills associated with data collection, designing controlled experiments and testing stated hypotheses, within microworlds for one physical science domain (density) impacted the acquisition of inquiry

A Data Mining Framework for Building Dengue Infection Disease Model
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Dengue infection is a virus-caused diseased that is spread by mosquitoes. Currently, there is no specific treatment, moreover there is no vaccine to prevent the people from the disease. Symptoms of this infection show rapid and violent to patients in a short time. Two

Inflectional morphology, reverse similarity and data mining–Finding and applying compact and transparent descriptions of verb systems of natural languages
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Abstract Under the term data mining, the field of computer science includes many different techniques for data analysis, among them methods of cluster analysis. In the approach presented, a special method is designed for the analysis of inflectional systems. The

ASSOCIATION RULE IN DATA MINING FOR LARGE TRANSACTIONAL DATABASE
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ABSTRACT Data mining is a technology to explore, analyze (knowledge discovery from data) the data and At last, extract the interesting (non-trivial, implicit, previously unknown and potentially useful) pattern or knowledge from huge amount of data. In this paper, we

AUTOMATED PROVISIONING OF CAMPAIGNS USING DATA MINING TECHNIQUES
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Abstract Today s telecom industry needs to use customer information for carrying out analysis, design and execution of new campaigns. The present and the traditional campaign generation process has identified few broad segments of customers based on some

Trajectory Data Mining and the Need for Semantics
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Abstract Due to the rapid advancements in technology, and the innovations in mobile, sensor, and GPS devices, increasing amounts of data related to moving objects has become available. Trajectory data mining is the application of conventional data mining techniques

Physics Performance Data Mining
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A Johns ABSTRACT Physics is one of the most important fields of study in the world. By identifying correlations between students and their knowledge of physics we can greater understand how to keep advancing in physics as a society. Studying data is a very practical way to

A Data Mining Approach for Optimization of Acute Inflammation Therapy
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ABSTRACT Acute inflammation is a medical condition which occurs over seconds, minutes or hours and is characterized as a systemic inflammatory response to an infection. Delaying treatment by only one hour decreases patient chance of survival by about 7%. Therefore,

An Overview of Interaction Techniques and 3D Representations for Data Mining
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Since the emergence of databases in the 1960s, the volume of stored information has grown exponentially every year (Keim (2002)). This information accumulation in databases has motivated the development of a new research field: Knowledge Discovery in Databases (

MULTI-OBJECTIVE GENETIC-FUZZY DATA MINING*
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Abstract. Many approaches have been proposed for mining fuzzy association rules. The membership functions, which critically influence the final mining results, are difficult to define. In general, multiple criteria are considered when defining membership functions. In

Data Mining for a student database
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An academic year is divided into two semesters, during which the courses are taken according to the established curriculum. Some constrains between exams can be fixed in order to force students to take some exams in a specific order. Many students end up

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data mining and imdb



Extraction and integration of movielens and imdb data
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Abstract. This report describes the procedure followed for extracting and integrating Movie Lens and IMDb data. We firstly focus on data extraction, describing source schemas, target schemas and the algorithms that perform data extraction, data cleaning and data

Information visualization and proposing new interface for movie retrieval system (imdb
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Abstract This research studies the development of a new prototype of visualization in support of movie retrieval. The goal of information visualization is unveiling of large amounts of data orAbstract data set using visual presentation. With this knowledge the main goal is

Matching of MovieLens and IMDb movie titles
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Abstract. This report describes the procedure followed for joining MovieLens and IMDb databases. Even if both databases identify movie by title, unfortunately, they suffer from many problems such as abbreviation, translations into different languages and, generally,

Reviewing Romcom:(100) IMDb Users and (500) Days of Summer
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Abstract This article contributes to academic debates around the romantic comedy genre and comedy audiences by examining IMDb user reviews of (500) Days of Summer (2009). Directed by Marc Webb for Fox Searchlight Pictures,(500) Days of Summer was promoted

Genre Analysis of Newsgroup Movie Reviews on www. Imdb. com
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Movie reviews are considered one of the written discourses that contain essential information aiming to provide critical analysis of movies that are currently played. Movie reviews are widely read by readers who are interested in knowing whether the films that

Comparing IMDB Network of Actors to Random Graph Models
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We sought to determine whether there was/is an elite circle of actors in movies. To this end, we attempted to find a random graph model that represents the graph of actors connected by appearance in the same movie, which maintains the measure of clustering coefficient. We

Improving IMDb Movie Recommendations with Interactive Settings and Filters
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Abstract IMDb is a widely known online movie platform that offers movie information, allows to rate movies and recommends interesting movies to users. The IMDb movie recommendations do not however offer any means for interactivity or user control, which

IMDB Improved
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Abstract This project explores the implementation of predictors and recommenders. Of the many applications for recommenders, we will focus on learning the movie viewing patterns of different users with the goal of recommending movies to current or new users.

'One for the Horror Fans' vs.'An Insult to the Horror Genre': Negotiating Reading Strategies inIMDb Reviews of The Cabin in the Woods
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Movie Database (IMDb) reads:“Five friends go for a break at a remote cabin in the woods, where they get more than they bargained for. Together, they must discover the truth

Visualization and Recommendation of Similar Movies on the IMDB Movie Database
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ABSTRACT Exploring large graph structures is an important topic in the data mining and data visualization areas. This demo presents a novel technique for visualizing neighborhood and cluster relationships in graphs. Our technique works by projecting the original object

AToMPM Solution for the IMDB Case Study
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AToMPM al lows one to model and execute model transformations. It provides a graphical user interface to define the metamodels of the input and output languages, define the transformation rules and their scheduling, and execute continuously or stepby-step

Semantic Similarity Measurement: An Approach for Video Entities using IMDB
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ABSTRACT There have been a lot of researches on video high-level semantic modeling and analysis through schema and ontology. However, the lack of research about high-level semantic of video on the individual level makes it hard for us to compare videos.

Triadic Closure in the IMDB
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Abstract Social networks have certain properties that tend to influence the formation of relationships. Triadic closure is one of these properties, and has a tendency to exist in real social networks. Specifically, if three people have two relationships among one another,

When NEO meets the ORACLE: Predicting Collaboration and Movie Performance in IMDb
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Abstract Hollywood is a billion dollar industry and a main source of recreation for millions throughout the world. It is also the source of income for many who are related to the industry in one way or the other. Both these set of people wants the movie watcher to enjoy the

Predicting IMDB movie ratings using Google Trends
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Movie ratings are influenced by many factors, so accurate prediction of new movie ratings can be challenging. In recent years, various semantic analysis techniques were successfully applied to analyzing user reviews, which in turn were applied to predict IMDB movie

Filmler iin Yz Tanima Tabanli IMDB Eklentisi Face Recognition-based IMDB Plug-in for Movies
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Abstract In this paper, we present an initial study on an IMDB plug-in for cast identification in movies. In the system, training face images are collected by using Google image search. While watching a movie, the user clicks on the face of the person he is


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