Implementation of Real World Document Clustering Using BIRCH
Journal Title: International Journal for Research in Applied Science and Engineering Technology (IJRASET) - Year 2016, Vol 4, Issue 5
Abstract
Clustering is “the process of organizing objects into groups whose members are similar in some way”. A cluster is therefore a collection of objects which are coherent internally, but clearly dissimilar to the objects belonging to other clusters. In general, there are two common algorithms. The first one is the hierarchical based algorithm, which includes single link, complete linkage, group average and Ward's method. By aggregating or dividing, documents can be clustered into hierarchical structure, which is suitable for browsing. However, such an algorithm usually suffers from efficiency problems. The other algorithm is developed using the K-means algorithm and its variants. These algorithms can further be classified as hard or soft clustering algorithms. Hard clustering computes a hard assignment – each document is a member of exactly one cluster. The assignment of soft clustering algorithms is soft – a document’s assignment is a distribution over all clusters. In a soft assignment, a document has fractional membership in several clusters. The large variety of documents makes it almost unfeasible to create a general algorithm which can work best in case of all kinds of datasets.
Authors and Affiliations
Prof. Praveen Kumar Gautam, Mrs. Sunita N. Chaudhari
Keywords
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