Augusto Villa Monte, a Systems graduate from UNPL (Argentina), presented his doctoral thesis entitled “Automatic generation of texts with Soft Computing techniques”. Basically, it is a system that differentiates between what is essential and what is not, in a piece of writing. How does this work? Let’s see what the future holds for reading.
This is because, considering the exponential growth in the volume of textual information available in digital format. This doctor affirms that it is essential to have tools that facilitate the reading of texts. Because, as is normal, not all the information present in them has the same level of relevance, not only in terms of content, but also in terms of interest.
Automatic text summarization: an ideal solution for certain areas of knowledge
To solve the aforementioned problem, the researcher developed a solution to obtain text summaries automatically. In particular, for those areas of science, such as medicine, where research and information dissemination are essential for their development.
Villa Montes Explained:
“The thesis I presented develops two different strategies to build automatic text summaries, using Soft Computing techniques, which are used to solve problems that handle incomplete, uncertain or inaccurate information.”
He further added:
“The first of these strategies uses a particle-cluster optimization technique that, from the vector representation of the texts, constructs an extractive summary by appropriately combining several scoring metrics.”
“The second strategy, is related to the study of causality inspired by the management of uncertainty by fuzzy or fuzzy logic. Here, text analysis is performed through the construction of a graph (a set of objects called vertices or nodes linked by edges, representing binary relationships between elements) through which the most important causal relationships and the temporal restrictions that affect their interpretation are obtained”.
Finally, Villa Monte concluded:
“Both strategies fundamentally involve the classification of information and reduce the volume of the text, considering the receiver of the summary constructed in each case. On the one hand, the criteria used by the user to select the relevant parts of a document are identified. On the other hand, a graph is constructed from textual patterns useful for decision making”.
And you, do you think that in the future it will be possible to summarize texts automatically? Or better yet, do you think this is a necessary technology?
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