1,720,960 research outputs found
A new density based sampling to enhance DBSCAN clustering algorithm
No full textDBSCAN is one of the efficient density-based clustering algorithms. It is characterized by its ability to discover
clusters with different shapes and sizes, and to separate noise and outliers. However, when the dataset contain
different densities, DBSCAN clustering will be inefficient. In this paper, we propose an approach to enable
DBSCAN to cluster dataset having different densities by preprocess the dataset to make it with one density level.
This system composed of four stages: firstly, a new approach to separate dataset based on density is presented.
Secondly, a new density biased sampling technique is proposed. Thirdly, the resulted sparse data from the last two
stages is clustered with DBSCAN. Finally, the remaining data from sampling will be clustered with KNN. The
experimental results on synthetic and real datasets on average show that the clustering of the proposed algorithm is
better than that of DBSCAN by more than 7% and retains time complexity of DBSCAN
Combining the Attribute Oriented Induction and Graph Visualization to Enhancement Association Rules Interpretation
Get PDFThe important methods of data mining is large and from these methods is mining of association rule. The miningof association rule gives huge number of the rules. These huge rules make analyst consuming more time when searchingthrough the large rules for finding the interesting rules. One of the solutions for this problem is combing between one of theAssociation rules visualization method and generalization method. Association rules visualization method is graph-basedmethod. Generalization method is Attribute Oriented Induction algorithm (AOI). AOI after combing calls ModifiedAOI because it removes and changes in the steps of the traditional AOI. The graph technique after combing also callsgrouped graph method because it displays the aggregated that results rules from AOI. The results of this paper are ratio ofcompression that gives clarity of visualization. These results provide the ability for test and drill down in the rules orunderstand and roll up
Enhancing of DBSCAN based on Sampling and Densitybased Separation
Get PDFDBSCAN (Density-Based Clustering of Applications with Noise )is one of the attractive algorithms among densitybased clustering algorithms. It characterized by its ability to detect clusters of various sizes and shapes with the presence of noise, but its performance degrades when data have different densities .In this paper, we proposed a new technique to separate data based on its density with a new samplingtechnique , the purpose of these new techniques is for getting data with homogenous density .The experimental results onsynthetic data and real world data show that the new technique enhanced the clustering of DBSCAN to large extent
On the designing of two grains levels network intrusion detection system
No full textAbstractDespite the rapid progress of the information technology, protecting computers and networks remain a major problem for most authors. In this paper, two grains levels intrusion detection system (IDS) is suggested (fine-grained and coarse-grained). In normal case, where intrusions are not detected, the most suitable IDS level is the coarse-grained to increase IDS performance. As soon as any intrusion is detected by coarse-grained IDS, the fine-grained is activated to detect the possible attack details. Very fast decision tree algorithm is used in both of these detection levels. In order to ensure efficiency of the proposed model, it has been tested on KDD CUP 99 offline dataset and a real traffic dataset. Experimental results demonstrate that the proposed model is highly successful in detecting known and unknown attacks, and can be successfully adapted with packets' flow to increase IDS performance. This article explains how we got a detection rate greater than 93% with an average processing time equals to 3 × 10−6 s per example
Identifying Researchers’ Interest using Text Mining
Get PDFResearchers\u27 interests and academic journals are crucial for advancing scientific inquiry. Journals serve as platforms for sharing and validating discoveries, fostering a symbiotic relationship that advances our collective understanding and pushes the boundaries of human knowledge. Journals, which encompass natural edge research and establish benchmarks for academic rigor. In this paper, an analysis, using text mining, of the publications of Iraqi researchers in scientific journals is used to extract the researcher\u27s interest. In more detail, this paper utilizes the following technologies: pre-processing (tokenization, POS (“Part Of Speech”), normalization, case folding, lemmatization) – filtering (stop word elimination) - feature Extraction (TF-IDF), as well as classification using deep neural network classifier (DNNC), to address the problem of identifying the researcher\u27s interests through texts (title &abstract) analysis. The Iraqi researchers’ data in the field of computer science from the years 2010-2022. As obtained from the Scopus repository, a total of 1170 papers were collected via API- key and scrubber depending on the keyword of computer science and the year. Furthermore, these papers were manually classified based on the hierarchical classification of the ACM journal. Finally, the best results obtained from a classification using DNN and TF-IDF as classifying terms achieved a precision of 90%, Recall of 90%, f1-score of 90%, and accuracy of 90%
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Get PDF“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Get PDFWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
New trends in information and communications technology applications: third international conference, NTICT 2018, Baghdad, Iraq, October 2-4, 2018, proceedings
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