Document Clustering using Self-Organizing Maps
نویسندگان
چکیده
منابع مشابه
using game theory techniques in self-organizing maps training
شبکه خود سازمانده پرکاربردترین شبکه عصبی برای انجام خوشه بندی و کوانتیزه نمودن برداری است. از زمان معرفی این شبکه تاکنون، از این روش در مسائل مختلف در حوزه های گوناگون استفاده و توسعه ها و بهبودهای متعددی برای آن ارائه شده است. شبکه خودسازمانده از تعدادی سلول برای تخمین تابع توزیع الگوهای ورودی در فضای چندبعدی استفاده می کند. احتمال وجود سلول مرده مشکلی اساسی در الگوریتم شبکه خودسازمانده به حسا...
Self-Organizing Maps for Clustering in Document Image Analysis
In this chapter, we discuss the use of Self Organizing Maps (SOM) to deal with various tasks in Document Image Analysis. The SOM is a particular type of artificial neural network that computes, during the learning, an unsupervised clustering of the input data arranging the cluster centers in a lattice. After an overview of the previous applications of unsupervised learning in document image ana...
متن کاملWEBSOM - Self-organizing maps of document collections
Searching for relevant text documents has traditionally been based on keywords and Boolean expressions of them. Often the search results show high recall and low precision, or vice versa. Considerable eeorts have been made to develop alternative methods, but their practical applicability has been low. Powerful methods are needed for the exploration of miscellaneous document collections. The WEB...
متن کاملWEBSOM — Self-organizing maps of document collections1
With the WEBSOM method a textual document collection may be organized onto a graphical map display that provides an overview of the collection and facilitates interactive browsing. Interesting documents can be located on the map using a content-directed search. Each document is encoded as a histogram of word categories which are formed by the self-organizing map (SOM) algorithm based on the sim...
متن کاملUsing Growing hierarchical self-organizing maps for document classification
The self-organizing map has shown to be a stable neural network model for high-dimensional data analysis. However, its applicability is limited by the fact that some knowledge about the data is required to de ne the size of the network. In this paper we present the Growing Hierarchical SOM. This dynamically growing architecture evolves into a hierarchical structure of self-organizing maps accor...
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ژورنال
عنوان ژورنال: MENDEL
سال: 2017
ISSN: 2571-3701,1803-3814
DOI: 10.13164/mendel.2017.1.111