Timo Honkela

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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(More)
Kohonen's Self-Organizing Map (SOM) is one of the most popular arti cial neural network algorithms. Word category maps are SOMs that have been organized according to word similarities, measured by the similarity of the short contexts of the words. Conceptually interrelated words tend to fall into the same or neighboring map nodes. Nodes may thus be viewed(More)
Semantic roles of words in natural languages are reeected by the contexts in which they occur. These roles can explicitly be visualized by the Self-Organizing Map (SOM). In the experiments reported in this work the source data consisted of the raw text of Grimm fairy tales without any prior syntactic or semantic categorization of the words. The algorithm(More)
On January 19, 1996 we published in the Internet a demo of how to use Self-Organizing Maps (SOMs) for the organization of large collections of full-text les. Later we added other newsgroups to the demo. It can be found at the address http://websom.hut../websom/. In the present paper we describe the main features of this system, called the WEBSOM, as well as(More)
|Formulation of suitable search expressions for information retrieval from large full-text databases may currently require considerable eeorts. Changing the scope of the search when, e.g., too many or too few hits have been obtained, requires re-formulation of the search expression. For an alternative scheme we suggest an explorative full-text information(More)
Powerful methods for interactive exploration and search from collections of free-form textual documents are needed to manage the ever-increasing flood of digital information. In this article we present a method, WEBSOM, for automatic organization of full-text document collections using the self-organizing map (SOM) algorithm. The document collection is(More)
New methods that are user-friendly and efficient are needed for guidanceamong the masses of textual information available in the Internet and theWorld Wide Web. We have developed a method and a tool called the WEBSOMwhich utilizes the self-organizing map algorithm (SOM) for organizing largecollections of text documents onto visual document maps. The(More)
We present Likey, a language-independent keyphrase extraction method based on statistical analysis and the use of a reference corpus. Likey has a very light-weight preprocessing phase and no parameters to be tuned. Thus, it is not restricted to any single language or language family. We test Likey having exactly the same configuration with 11 European(More)