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A self-organizing semantic map for information retrieval

Xia Lin, Dagobert Soergel, Gary Marchionini
1991 Proceedings of the 14th annual international ACM SIGIR conference on Research and development in information retrieval - SIGIR '91  
A SELF-ORGANIZING SEMANTIC MAP FOR AI LITERATURE Kohonen's self-organizing map algorithm is applied to a collection of documents from the LISA database.  ...  The document vectors are used as input to train a feature map of 25 features and 140 nodes. z Following the Kohonen's algorithm: o each feature corresponds to a selected word, Qeach document is an input  ... 
doi:10.1145/122860.122887 dblp:conf/sigir/LinSM91 fatcat:a6f2oj6da5enljmjvl5ctrzxsu

A self organizing document map algorithm for large scale hyperlinked data inspired by neuronal migration

Kotaro Nakayama, Yutaka Matsuo
2011 Proceedings of the 20th international conference companion on World wide web - WWW '11  
In this research, we pay attention to SOMs (Self Organizing Maps) because of their capability of visualized clustering that helps users to investigate characteristics of data in detail.  ...  In this paper, we describe the algorithm and implementation, and show the practicality of the algorithm by applying MIGSOM to a huge scale real data set: Wikipedia's hyperlink data.  ...  MIGSOM is also an interactive learning algorithm like Kohonen's, but the data structure and process are different and novel.  ... 
doi:10.1145/1963192.1963241 dblp:conf/www/NakayamaM11 fatcat:xsmy73vu7jhubktav27gu7t2iq

A Bilingual Numeral OCR System for Creating Uni-Lingual Digitized Numeral Document

Karthick K, Chitra S
2015 Modern Applied Science  
The Kohonen's self-organizing map (SOM) based recognition system has been used for recognizing the numerals and recognized characters in bilingual numerals (Tamil and European Numerals) form are converted  ...  In this paper, the image which contains printed Tamil and European numerals has been recognized using common OCR System and the Tamil numerals are converted into European numerals to globalize the document  ...  In this paper, the mixture of isolated Tamil and European numerals image is recognized using Kohonen's self-organizing map and converted into European numerals in order to globalize the bilingual document  ... 
doi:10.5539/mas.v9n13p148 fatcat:kynfbsbjmrcopbzlaadpufmhqi

Mapping weblog communities [article]

Juan-J. Merelo-Guervos, Beatriz Prieto, Fatima Rateb, Fernando Tricas
2003 arXiv   pre-print
In this paper, we will map a network of websites using Kohonen's self-organizing map (SOM), a neural-net like method generally used for clustering and visualization of complex data sets.  ...  In this paper we show how SOM discovers interesting community features, its relation with other community-discovering algorithms, and the way it highlights the set of communities formed over the network  ...  The algorithm was run 30 times with the same parameters, but different Table 2 : . Parameters used to train Kohonen's self-organizing map in this paper.  ... 
arXiv:cs/0312047v1 fatcat:os44kh7nkzbupbtshp7wqoxzmm

Using Self-Organizing Maps for Sentiment Analysis [article]

Anuj Sharma, Shubhamoy Dey
2013 arXiv   pre-print
For supervised sentiment analysis, a competitive learning algorithm known as Learning Vector Quantization is used.  ...  Specifically, this paper implements the SOM algorithm for both supervised and unsupervised learning from text documents.  ...  The Multi-Pass LVQ performed best among all algorithms with 89.1% overall accuracy. The (classic Kohonen's) SOM was the worst performer among all. Fig. 3.  ... 
arXiv:1309.3946v1 fatcat:k6brxzbyonhe3j534aojizfexu

A Neural Network Approach to Medical Image Segmentation and Three-Dimensional Reconstruction [chapter]

Vitoantonio Bevilacqua, Giuseppe Mastronardi, Mario Marinelli
2006 Lecture Notes in Computer Science  
Moreover it generates a three-dimensional model of the segmented region using Direct3D.  ...  In this work, was proposed a neural network segmentation based on Self-Organizing Maps (SOM) and a three-dimensional SOM architecture to create a 3D model, starting from 2D data of extracted contours.  ...  We have used two main techniques based on the first approach: Thresholding and a Neural Network segmentation based on Kohonen's Self-Organizing Maps.  ... 
doi:10.1007/11816157_3 fatcat:6eaw7zdn5nen3pdro42iyy3hja

Empirical Studies On Machine Learning Based Text Classification Algorithms

Shweta C. Dharmadhikari, Maya Ingle, Parag Kulkarni
2011 Advanced Computing An International Journal  
Automatic classification of text documents has become an important research issue now days.  ...  We expect our research efforts provide useful insights on the relationships among various text classification techniques as well as sheds light on the future research trend in this domain.  ...  E Kohonen's Self Organizing Network It uses a special type of neural network called Kohonen's self-organizing network.  ... 
doi:10.5121/acij.2011.2615 fatcat:s2x4tdqknrb3phftvutykyayey

Authorship Categorization With Neural Network

Nesibe Merve Demir
2012 Southeast Europe Journal of Soft Computing  
Choosing the algorithm and descriptors are important issues in the research.  ...  Artificial neural network is proposed to classify the texts of authors using a set of lexical descriptors and feed-forward neural network using back propagation.  ...  KOHONEN'S SELF ORGANIZING MAP As a clustering technique, Kohonen's self organizing Map (SOM) method finds similar data to another or dissimilar data to another data.  ... 
doi:10.21533/scjournal.v1i2.62 fatcat:h4mmzw57yjhmpiskdkw6hrkkp4

Automatic extraction of relationships between terms by means of Kohonen's algorithm

Vicente P. Guerrero, Félix Moya-Anegón, Victor Herrero-Solana
2002 Library & Information Science Research  
First, the vector model is used to represent the terms as vectors according to which documents they appear in.  ...  Second, these vectors are used as the input to a Kohonen network, which organizes them topologically.  ...  The algorithm then functions during learning according to Kohonen's original picture.  ... 
doi:10.1016/s0740-8188(02)00124-x fatcat:dtiuaptbevenrm2ire452g262u

Self-Organization by Optimizing Free-Energy

Jakob J. Verbeek, Nikos A. Vlassis, Ben J. A. Kröse
2003 The European Symposium on Artificial Neural Networks  
The algorithm is similar to Kohonen's Self-Organizing Map algorithm and not limited to Gaussian mixtures.  ...  We illustrate the algorithm with an application on word clustering.  ...  We presented a penalized log-likelihood probabilistic mixture modeling method, similar to Kohonen's SOM.  ... 
dblp:conf/esann/VerbeekVK03 fatcat:74r6wdjq55abjjtal6uwc4umty

Self-organizing mixture models

J.J. Verbeek, N. Vlassis, B.J.A. Kröse
2005 Neurocomputing  
self-organization.  ...  Compared to other mixture model approaches to self-organizing maps (SOMs), the function our algorithm maximizes has a clear interpretation: it sums data log-likelihood and a penalty term that enforces  ...  We like to thank the organizers of ESANN 2003 for inviting us to submit this extended version of our paper [27] to Neurocomputing.  ... 
doi:10.1016/j.neucom.2004.04.008 fatcat:7tq6ypduqfcpfod5uo5u6r36de

A dynamic neural field mechanism for self-organization

Lucian Alecu, Hervé Frezza-Buet
2009 BMC Neuroscience  
In order to solve this task with neural fields, we adapt the Kohonen's classical self-organizing maps (SOM) algorithm [7] and propose the following 3-layers architecture.  ...  Motivation Aiming to extend the applicative area of DNF, we are hereby interested in using this computational model to implement self-organizing mechanisms.  ...  In order to solve this task with neural fields, we adapt the Kohonen's classical self-organizing maps (SOM) algorithm [7] and propose the following 3-layers architecture.  ... 
doi:10.1186/1471-2202-10-s1-p273 fatcat:xrvptl3wobcdro6c2fksx6jmk4

The New and Computationally Efficient MIL-SOM Algorithm: Potential Benefits for Visualization and Analysis of a Large-Scale High-Dimensional Clinically Acquired Geographic Data

Tonny J. Oyana, Luke E. K. Achenie, Joon Heo
2012 Computational and Mathematical Methods in Medicine  
The objective of this paper is to introduce an efficient algorithm, namely, the mathematically improved learning-self organizing map (MIL-SOM) algorithm, which speeds up the self-organizing map (SOM) training  ...  In the proposed MIL-SOM algorithm, the weights of Kohonen's SOM are based on the proportional-integral-derivative (PID) controller.  ...  These timely critiques of the MIL-SOM algorithm facilitated its design, implementation, and enhanced its overall quality.  ... 
doi:10.1155/2012/683265 pmid:22481977 pmcid:PMC3314187 fatcat:ntonkibiofbojol5ub44mez6li

Comparison of neural models for document clustering

Vicente P. Guerrero-Bote, Cristina López-Pujalte, Félix de Moya-Anegón, Victor Herrero-Solana
2003 International Journal of Approximate Reasoning  
The best results were found with Kohonen's algorithm which also organizes the clusters topologically. We end by discussing in more detail the possibilities offered by Kohonen's algorithm.  ...  We compared the application of different algorithms to document clustering.  ...  Document vectorization/document representation: The next step was to apply the vector space model to transform these documents into vectors that one could use as inputs for the algorithms.  ... 
doi:10.1016/j.ijar.2003.07.012 fatcat:3skzyzdoirhl7i4fanz5rkvtee

Web page clustering using a self-organizing map of user navigation patterns

Kate A. Smith, Alan Ng
2003 Decision Support Systems  
We have developed LOGSOM, a system that utilizes Kohonen's self-organizing map to organize web pages into a two-dimensional map.  ...  In this paper, we evaluate the feasibility of using a self-organizing map (SOM) to mine web log data and provide a visual tool to assist user navigation.  ...  Conclusion We have presented LOGSOM, a system that utilizes Kohonen's self-organizing map to organize web documents in a domain onto a two-dimensional map.  ... 
doi:10.1016/s0167-9236(02)00109-4 fatcat:fzgjmx24evehxjhfa4x4ihcrz4
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