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This paper investigates an efficient modal method for reducing weak transmission stability boundaries and identifying voltage control areas. This method divides the power system network into regions to eventually reduce the control candidates for each controller and minimize the interaction between each voltage control area. To determine the optimized number of areas, proper selection of threshold...
When studies in literature are examined, it is seen that different approaches have been used to solve facility layout problems. The relationship between departments in layout is always important. In this study, data mining technique is used for analyzing relations among departments and then association rules are obtained. Determining closeness relationships between the departments in facility are...
We present a new algorithm for discovering clusters in noisy data streams using dynamic and cluster-specific temporal decay factors. Our improvement helps identify and adapt to evolving trends by adapting the weighting of stream data based on both content attributes and temporal arrival patterns. Our experimental results show that the proposed algorithm can discover better quality clusters in noisy...
The Levy Walk (or Levy flight) is a concept fromBiomathematics to describe the hunting–behaviour of manypredatory species. It is a very efficient way to find prey in avery short time frame. We now want to use this concept ina clustering–context to – if you so will – "hunt" for clusters. We describe how we convert this concept into an efficient wayto find cluster centres by linking the data...
A challenge task of data mining is to process massive data in the big data era. MapReduce is an attractive model to overcome this challenge. This paper presents a new method to accelerate the process of learning Markov blanket Bayesian network(MBBN). Markov blanket is a better model type of Bayesian network in some complex datasets. The time and space cost of learning Markov blanket is large, and...
The watershed rehabilitation success rate have not been up, is the result of policies in watershed rehabilitation strategies that are less precise. From the above problems, we need a study that can provide a reference or any other alternative in determining priority watersheds to be rehabilitated, one through data mining. This paper uses a case study of Watershed data which are grouped using K-modes...
With the rapid growth of Internet consumption, the various product comments' form and redundant information are not convenient for the customers to grasp the hot opinions of the historical comments. In view of this, this paper studies the hot opinions of the products' comments and takes the hotel comments data as the main research objects. We filter the comment data from the length of the comments...
With the expansion of World Wide Web services due to the growing explosion of information during these recent years automatic summarization has become primordial to provide efficient mechanisms to resume and present effective textual information. This technology can summarize multiple or single documents to get a summary. In this paper we develop method based on Fuzzy ontology extraction technique...
To extract knowledge from Data bases Data mining is being used. Data mining is associated with various techniques. In those Clustering is considered to be one of the best approaches. Clustering a huge data set specifically categorical data is difficult and tedious procedure. In this context a proficient method is proposed that is focused on Rough purity for humanizing accuracy of grouping and keeping...
The rapid computerization and advancement in the technology has led to huge amount of data in the databases. Research has shown that the amount of data in the world doubles in every 20 months. However, this available data consists of large number of noise values and thus, cannot be directly used. The extraction of information from the vast pool of data has emerged a major challenge.
Online Social Networks (OSNs) provide platform to raise opinions on various issues, create and spread news rapidly in Online Social Network Forums (OSNFs). This work proposes a novel method for Profiling Forum Users (PFU) by exploring their behavioral characteristics based on their involvement in various topics of discussion and number of posts in respective topics posted by them in OSNFs dynamically...
This paper proposes a fuzzy relational clustering (FRC) to find similar sentences from a set of sentences as well as group them in clusters. For finding similar sentences here FRC used both word-to-word and order similarity. For word-to-word similarity FRC used Jiang and Conrath similarity measure (JnC) with the help of WordNet database. Order similarity is calculated from joint word set. As a sentence...
Outlier detection is an important issue in the realm of data mining. Several applications relay on outlier detection such as intrusion detection, fraud detection, medical and public health data, image processing, etc. Clustering-based outlier detection algorithms are considered as the most important outlier detection approaches. They provide high detection rate, however, they suffer from high false...
Classification is one of important tasks in the Data Mining field. It aims to merge the similar data into a group. In this context, several methods of classification have been proposed in literature. DENCLUE (DENsity-based CLUstEring) is one of the most effective unsupervised classification methods, that allows to classify voluminous data. This method is based on the concept of density and the Hill...
Data mining advances as a promising solution in exploring knowledge concealed in database and clustering is one its application. Clustering can be explained as the unconfirmed categorization of patterns into groups. It is the task of combining a set of objects into diverse subsets such that objects belonging to the similar cluster are extremely related to each other. Various objective functions are...
The unsupervised analysis of data-sets, both large in dimension as well as in number of objects, are one of the most challenging tasks in data intense sciences. Especially in astronomy, dedicated survey telescopes generate an enormous amount of complex data. For example the database of the Sloan Digital Sky Survey (SDSS DR10) contains 3 million spectra with ca. 5,000 values each. Analyzing those spectra...
Virtualization brought an immense commute in the modern technology especially in computer networks since last decade. The enormity of big data has led the massive graphs to be increased in size exponentially in recent years so that normal tools and algorithms are going weak to process it. Size diminution of the massive graphs is a big challenge in the current era and extraction of useful information...
A content delivery network (CDN) using community information that is extracted from the data of a social networking service (SNS) is proposed in this paper. The structure of the load characteristics of the CDN in terms of the number of servers, communities, and downloads is also shown as a tool for evaluating network performance.
This paper describes a methodology for the design of a supervisory system applied to a biotechnological process. A discrete-event system (DES) is build by the joint participation of the process expert along with clustering and classification techniques applied to measured signals. The automaton becomes a heuristic model of the process under supervision. In the application example, a yeast batch culture,...
The STC algorithm clusters the documents based on shared phrases and it is a linear time algorithm. Directed against the insufficiency of the existing STC algorithm such as the quality of clustering results and the screening of the clustering labels, the paper improves STC algorithm, respectively perfecting the choice of the base cluster, the similarity calculation formula used to merge the base clusters...
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