The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
In this digital world, we are facing the flood of data, but depriving for knowledge. The eminent need of mining is useful to extract the hidden pattern from the wide availability of vast amount of data. Clustering is one such useful mining tool to handle this unfavorable situation by carrying out crucial steps refers as cluster analysis. It is the process of a grouping of patterns into clusters based...
Data mining techniques have been found useful in understanding and enhancing student performance as well as decision making related to teaching and learning in HEIs. Literature review enabled the choice of time to degree and cumulative grade point average (CGPA) as examples of student performance factors for investigation. Student features that could be extracted using SQL query from student dataset...
Trajectories of moving objects provide crucial clues for video event analysis especially in surveillance applications. In this paper, we proposed a novel approach for detecting abnormal events in video surveillance. Our approach is based on trajectory analysis involving two phases. In the first phase, we extracted clusters of normal events through an agglomerative hierarchical clustering of saved...
To protect computer networks from attacks and hackers, an intrusion detection system (IDS) should be integrated in the security architecture. Although the detection of intrusions and attacks is the ultimate goal, IDSs generate a huge amount of false alerts which cannot be properly managed by the administrator, along with many noisy alerts or outliers. Many research works were conducted to improve...
In analytical optical character recognition, effects of noise and overlapping character blocks constitute a major problem to feature extraction algorithms. This problem degrades the performance of the recognition stage. In this approach, an adaptive clustering algorithm and Hamming Distance computation are proposed to aid the extraction and recognition processes. Initially a line is picked from the...
This paper proposes a clustering based image segmentation approach for elephant recognition. Appreciable recognition rate was achieved by k-means clustering technique followed by feature extraction and K nearest neighbour (K-NN) classifier. The k-means algorithm employs the concept of fitness and belongingness to provide a more adaptive andbetterclustering process as compared to several conventional...
We are currently working on the concept of an omni script and interactive word retrieval system for ancient document collection navigation, based on query composition for non-expert users. To make the query, the user selects and composes writing pieces, which are invariants automatically extracted from the old document collection. In order to extract invariants from documents, strokes must be first...
Transfer learning is a most important research area within information retrieval. As we know, there are different types of data available everywhere and among those, dealing with unstructured data is quite difficult. This paper focuses on dealing with unstructured data. Social challenge is, any nonmedical background person also uses this system for prediction of patient disease. This paper utilizes...
Clustering task aims at the unsupervised classification of patterns in different groups. Clustering problem has been approached from different disciplines. Many Swarm Intelligence algorithms have been developed to solve numerical and combinatorial problems. Clustering with swarm-based algorithms especially Ant colony algorithm is have been shown better results in a variety of real world application...
Proteins are the structural components of living cells and tissues, and thus an important building block in all living organisms. Patterns in proteins sequences are some subsequences which appear frequently. Patterns often denote important functional regions in proteins and can be used to characterize a protein family or discover the function of proteins. Moreover, it provides valuable information...
This paper addresses the ongoing issue of tone error detection for Mandarin Computer Assisted Language Learning (CALL) systems. A novel approach based on clustering is proposed. The selection of different contextual tonal factors including Uni-tone, LBi-tone and RBi-tone are explored. Experimental results show that our proposed approach is feasible, obtaining an Equal Error Rate (EER) of 18.75% by...
Categorizing visitors based on their navigation patterns on a website is a key problem in electronic logistics. However, user navigation data and feature vector extracted from it are sparse, and traditional clustering method doesn't solve this problem satisfactorily. As a step forward, a closed repetitive gapped subsequence mining based navigation pattern clustering method is proposed. Feature vector...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.