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Visualization of text document corpus
Blaz Fortuna, Dunja Mladenić and Marko Grobelnik
In: SIKDD 2005 at multiconference IS 2005, 17 Oct 2005, Ljubljana, Slovenia.
AbstractFrom the automated text processing point of view, natural
language is very redundant in the sense that many different
words share a common or similar meaning. For computer
this can be hard to understand without some background
knowledge. Latent Semantic Indexing (LSI) is a technique
that helps in extracting some of this background knowledge
from corpus of text documents. This can be also viewed as
extraction of hidden semantic concepts from text
documents. On the other hand visualization can be very
helpful in data analysis, for instance, for finding main
topics that appear in larger sets of documents. Extraction of
main concepts from documents using techniques such as
LSI, can make the results of visualizations more useful. For
example, given a set of descriptions of European Research
projects (6FP) one can find main areas that these projects
cover including semantic web, e-learning, security, etc. In
this paper we describe a method for visualization of
document corpus based on LSI, the system implementing it
and give results of using the system on several datasets. [Edit]
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