Top Research Papers on Data Mining

TH-Miner system includes the visualization clustering tool, classification tool, sequence pattern finder and text categorizer, which realizes several classical data mining arithmetic and constructs several new methods.

The goal of DT-miner is to provide a highly interactive, user-centered environment for the exploration of significant association rules according to users' interests, and to significantly benefit from association rule metrics that improve user understanding of the information base and can inform the selections he makes.

The minitrack covers the broad theory and application issues related to data mining, machine learning, knowledge acquisition, knowledge discovery, information retrieval, data base, and inductive decision-making. Both structured and unstructured data repositories including human expert decisions, environmental/normative datasets, large document collections, and web databases are considered. Theoretical and methodological exploration in the previous years motivates us to further investigate the various and richer data and knowledge representation schemes such as Web, multimedia, and geographic d...

The heated debate regarding not only its value in the public safety community but also whether data mining reflects an ethical, or even legal, approach to the analysis of crime and intelligence data is confounding the question of whether to acquire data mining technology.

The method comprises setting data mining workflow, said workflow comprising a plurality of parallel data processing task, and activating the workflow, and said plurality of when parallel dataprocessing task is triggered can improve the efficiency of data mining.

The intrepid data miner runs many risks, such as being buried under mountains of data or vanishing along with the "mysterious disappearing terabyte”.

This demo presents Pattern-Miner, an integrated environment for pattern management and mining that deals with the whole lifecycle of patterns, from their generation (using data mining techniques) to their storage and querying, putting also emphasis on the comparison between patterns and meta-mining operations over the extracted patterns.

The extraction of mineral resources from the earth, in various mining forms, such as open-cast and underground mining, has significant environmental and societal consequences, both during and after mining operations. It results in habitat destruction, soil erosion, deforestation, biodiversity loss, and the release of harmful pollutants into the environment. These pollutants, including heavy metals and sulphur compounds, etc., which contaminate water sources and soil, posing a serious threat to ecosystems and human health. Despite these challenges, mining remains essential for providing raw mat...

This paper analyzes the challenges involved in designing data mining techniques for mining data streams besides evaluating various existing techniques and their preprocessing methods to reveal which methods are feasible and which methods are not feasible in real-time data streaming applications.

Data mining is a field of intersection of computer science and statistics used to discover patterns in the information bank to extract useful information from the dossier of data and mold it into an understandable structure for future use.

It turns out that Oracle is better with working with larger datasets while Weka is more accurate with smaller datasets, and Orcale, however, sacrifaces accuracy in order to be capable of always building a model.

The invention relates to a data mining system and the data mining method which can be used for analyzing business data from multiple views and multiple granularities.

It is generally observed throughout the world that in the last two decades, while the average speed of computers has almost doubled in a span of around eighteen months, theaverage speed of the network has doubled merely in a spans of just eight months.

Die für die Prozessanalyse relevanten softwaretechnischen and methodischen Aspekte des Data Mining werden diskutiert and entsprechende Anwendungsworkflows exemplarisch am Beispiel eines biotechnischen Produktionsprozess sowie eines Polymerprozesses demonstriert.

A new spatial data mining known as SD-Miner is proposed, which consists of three parts: graphical interface for input and output, the data storage module using DBMS, and a data mining module for spatial data mining function.

A methodology for search of temporal patterns, which is tested on the problem of difference between hepatitis B and C proves that the suggested general methodology has promising potential when applied to the considered type of data.

The utility of *Miner for thematic information extraction from multisource spatiotemporal data (remote sensing images and ancillary geospatial databases) is shown.

An overview of application of data mining techniques such as decision tree is provided and progressive applications in addition to existing gap and less considered area are revealed and determines the future works for researchers.

The theory of mind concept known from studies in animal behavior is adopted and adapted for expressive user modeling and becomes knowledge discovery going beyond the human’s knowledge and covering domain-specific insights.

SD-Miner supports users to perform non-spatial data mining functionalities as well as spatial datamining functionalities intuitively and effectively and provides users with spatial data mining functions as a form of libraries, thereby making applications conveniently use those functions.

This guide toodes explains how to model, score, and modify Nodes to improve the quality and efficiency of the network.

The experimental results directs that the sampling of Ant-Miner algorithm can efficiently solve the problems of mining the data in JSSP environment.

This book presents the most common techniques used in data mining in a simple and easy to understand way through one of the most most common software solutions from existing in the market, namely the SAS software.

This chapter discusses methodological approaches to data mining, applications in science, engineering and life sciences, and neural networks and decision trees.

Significant segments of recent data mining research that feed into semantic data mining are reviewed and some promising application areas are described, national security and web mining being foremost among these.

Various fault detec tion techniques in the mobile communication with data mining are described and it is demonstrated that data mining can be used to identify mobile communication fraud, improve marketing effectiveness, and identify network faults.

All possible techniques and operations involved in data mining are put forth and will compare them in order to find the advantages and disadvantages of different methods.

The role of information mining for information extraction in web page, structure and usages mining in current web models is examined, and the method of extracting patterns from information is outlined, and data processing question languages will be designed.

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: Data mining comes from mining, that is, the extraction of minerals from the Earth. On the occasion of the retirement of Prof. Nina Thornhill, a pioneer in the are of data mining techniques in the process industries, the authors are exploring the similarities of mining data and mining rock, are establishing the current state of mining data in minerals processing plants and summarizing lessons learnt over the years. Despite advances made, there are still opportunities for research to automate data mining in an industrial context.

This chapter focuses on the challenges that appear when the data is large and the computations complex, and can be thought o f a s algorithms for executing very complex queries on non-main-memory data.

This paper applied classification algorithm for coal mines dataset, and discussed decision tree, nearest neighbor classifier, NN classifier for prediction of class label.

Kmeans, SVM and Naïve Bayes algorithms are analysed in detail to observe the accuracy and response time both on concept and empirical perspective to compare traditional mining with Big data mining.

Free open source software like Keel, KNIME, RapidMiner, Weka, Tanagra, and Orange are explained and compared and the free open source and the proprietary data mining tool is compared.

The knowledge discovery process in both the techniques is compared by developing a classification model using Naive bayes classifier and the former case uses Edu-data, a data collected from technical education system and the latter case uses massive online analysis frame work to generate the data streams.

The problem of distributed data mining is very important in network problems, and systems that explicitly take this into account are needed, by combining data mining with game theory.

This paper was written to review existing papers regarding data mining, especially classification, to get information and map from research that has been done to be used as literature on the author's research plan.

Using business process data mapping (BPDM) to define the targeted data along with the process of knowledge discovery mapping in the database may provide a more targeted approach with much lest costs expended.

This study gives insight into a data-driven framework for modern mines and presents a data mining implementation on real-time mining-related data for prediction of blasting performance, using random forest and adaptive boosting algorithm on an integrated data warehouse.

From the point of evolution from data to knowledge, some concepts of database, data mining and knowledge discovery, and their relationships are elaborated, and the model architecture of Data Mining system is described.

This paper examines the interesting perspective of "ILP-based MRDM for FDM" and provides justification and observations, and reports results of related experiments.

A new spatial data mining system is proposed through the use of database management system to store and manage spatial data and non-spatial data model for data storage.

This study aims to show how the footage of the film "The Night Comes for Us" displays and reflects the image of Indonesia based on Jean Baudrillard's imaging model that starts from the stages of representation, ideology, simulation and simulakra.

Netflix adalah sebuah platform streaming yang menyajikan Netflix original movie dan series , Konten yang diproduksi oleh Netflix dan bekerjasama dengan sineas global (Global Film Maker) sebagai keunggulan dibandingkan dengan langganan streaming lainnya. Netflix mengajak penontonnya untuk mengenal kebudayaan global dengan film-film orginalnya. Di Indonesia, Netflix secara resmi dan perdana ini merilis Netflix original movie dengan judul “The Night Comes for Us”. Penelitian ini bertujuan untuk menunjukkan bagaimana cuplikan film “The Night Comes for Us” menampilkan dan merefleksikan citra Indone...

This paper focuses on the applications of data mining in the field of education and implementation of three widely used data mining techniques using Rapid Miner on the data collected through a survey.

Based on the abundant research of domestic and oversea materials, this artlcle systematically mastered the development and application of the imaging spectrum technology and a processing diagram of data mining and mineral mapping was achieved.

Analysis of relationship between traffic data implied information comprehensively will help manage data scientifically and reasonably for traffic management departments and users to provide convenient transportation and to promote information development for transportation.

Active faults are sources of earthquakes and one of them is north fault of Tabriz in the northwest of Iran. The activation of faults can harm humans’ life and constructions. The analysis of the seismic data in active regions can be helpful in dealing with earthquake hazards and devising prevention strategies. In this chapter, structure of earthquake events along with application of various intelligent data mining algorithms for earthquake prediction are studied. Main focus is on categorizing the seismic data of local regions according to the events’ location using clustering algorithms for cla...

The graduate certificate’s narrow focus allows you to dig deep into this specific topic, and start applying your knowledge sooner, so you can more easily fit it into your busy life.

An overview of the fast growing field of Knowledge Discovery in Database (KDD) and Data Mining and techniques of data mining are presented.