A fuzzy clustering approach for finding similar documents using a novel similarity measure
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Efficient Phrase-Based Document Similarity for Clustering
IEEE Transactions on Knowledge and Data Engineering
Clustering of document collection - A weighting approach
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Using the self organizing map for clustering of text documents
Expert Systems with Applications: An International Journal
Fast Query Point Movement Techniques for Large CBIR Systems
IEEE Transactions on Knowledge and Data Engineering
Indexing 3-D human motion repositories for content-based retrieval
IEEE Transactions on Information Technology in Biomedicine - Special section on computational intelligence in medical systems
Content based image retrieval using unclean positive examples
IEEE Transactions on Image Processing
Recurrent-neural-network-based Boolean factor analysis and its application to word clustering
IEEE Transactions on Neural Networks
Generic title labeling for clustered documents
Expert Systems with Applications: An International Journal
Expert system for color image retrieval
Expert Systems with Applications: An International Journal
An Efficient Concept-Based Mining Model for Enhancing Text Clustering
IEEE Transactions on Knowledge and Data Engineering
Hierarchical fuzzy clustering decision tree for classifying recipes of ion implanter
Expert Systems with Applications: An International Journal
Text stream clustering algorithm based on adaptive feature selection
Expert Systems with Applications: An International Journal
Multilabel Neighborhood Propagation for Region-Based Image Retrieval
IEEE Transactions on Multimedia
Active Learning Methods for Interactive Image Retrieval
IEEE Transactions on Image Processing
Fast K-means algorithm based on a level histogram for image retrieval
Expert Systems with Applications: An International Journal
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Clustering of related or similar objects has long been regarded as a potentially useful contribution of helping users to navigate an information space such as a document collection. Many clustering algorithms and techniques have been developed and implemented but as the sizes of document collections have grown these techniques have not been scaled to large collections because of their computational overhead. To solve this problem, the proposed system concentrates on an interactive text clustering methodology, probability based topic oriented and semi-supervised document clustering. Recently, as web and various documents contain both text and large number of images, the proposed system concentrates on content-based image retrieval (CBIR) for image clustering to give additional effect to the document clustering approach. It suggests two kinds of indexing keys, major colour sets (MCS) and distribution block signature (DBS) to prune away the irrelevant images to given query image. Major colour sets are related with colour information while distribution block signatures are related with spatial information. After successively applying these filters to a large database, only small amount of high potential candidates that are somewhat similar to that of query image are identified. Then, the system uses quad modelling method (QM) to set the initial weight of two-dimensional cells in query image according to each major colour and retrieve more similar images through similarity association function associated with the weights. The proposed system evaluates the system efficiency by implementing and testing the clustering results with Dbscan and K-means clustering algorithms. Experiment shows that the proposed document clustering algorithm performs with an average efficiency of 94.4% for various document categories.