We have developed a novel system for content-based image retrieval in large, unannotated databases. The system is called PicSOM, and it is based on tree structured self-organizing maps (TS-SOMs). Given a set of reference images, PicSOM is able to retrieve another set of images which are similar to the given ones. Each TS-SOM is formed with a di€erent image feature representation like color, tex...

DNA microarrays provide a powerful means of monitoring thousands of gene expression levels at the same time. They consist of high dimensional data sets which challenge conventional clustering methods. The data’s high dimensionality calls for Self Organizing Maps (SOMs) to cluster DNA microarray data. This paper shows that a precise estimation of the variables’ variances is, however, the key to ...

The induced pluripotent cells (iPSCs) are derived from somatic cells by reprogramming their genetic profiles. Such a process requires coordinated dynamic expression of hundreds of genes and proteins. As both deterministic and stochastic elements control the reprogramming process, it is not easy to have a way to reflect the status of gene regulatory network in those reprogramming cells. In this ...

For databases of facial images, where each subject has only a few images, the query precision of interactive retrieval suffers from the problem of extremely small class sizes. A novel method is proposed to relieve this problem by applying partial relevance to the interactive retrieval. This work extends an existing content-based image retrieval system, PicSOM, by relaxing the relevance criterio...

In this paper, we present an approach for musical artist recommendation based on Self-Organizing Maps (SOMs) of artist reviews from Amazon web site. The Amazon reviews for the artists are obtained using the Amazon web service interface and stored in the form of textual documents that form the basis for the formation of the SOMs. The idea is to spatially organize these textual documents wherein ...

Content-based video navigation is an efficient method for browsing video information. A common approach is to cluster shots into groups and visualize them afterwards. In this paper, we present a prototype that follows in general this approach. Unlike the existing systems, the clustering is based on a growing self-organizing map algorithm. We focus on studying the applicability of SOMs for video...

We investigate whether it is possible to infer from implicit feedback what is relevant for a user in an information retrieval task. Eye movement signals are measured; they are very noisy but potentially contain rich hints about the current state and focus of attention of the user. In the experimental setting relevance is controlled by giving the user a specific search task, and the modeling goa...

Recently, a new method intended to realize conformal mappings has been published. Called Locally Linear Embedding (LLE), this method can map high-dimensional data lying on a manifold to a representation of lower dimensionality that preserves the angles. Although LLE is claimed to solve problems that are usually managed by neural networks like Kohonen’s Self-Organizing Maps (SOMs), the method re...

This paper aims to present a novel method of extracting bilingual lexica from comparable corpora using one of the artificial neural network algorithms, self-organizing maps (SOMs). The proposed method is very useful when a seed dictionary for translating source words into target words is insufficient. Our experiments have shown stunning results when contrasted with one of the other approaches. ...

Reprinted from This paper presents a computer dedicated to neu-ral algorithms. The computational core of the system is a systolic array of dedicated Processing Elements (PEs). This accelerator provides the primitives to implement several widely used neural models, including Kohonen's Self-Organizing Maps (SOMs). This paper concentrates on the problems related to the mapping of the SOM algorithm...