We have implemented a core summarizer of scientific articles written in Spanish, with the following components: a tokenizer, a grammar checker, a clarity checker, a cohesion-coherence checker, a common-topic extractor and an output formatter.
IT WILL WORK WITH A JAVA DEVELOPMENT KIT 1.7 ONLY !!!
This program is a data-miner and a knowledge-miner. It does exactly the opposite of what the text summarizers do. A text summarizer produces a shortened text given some text as an input. An inverse summarizer takes the shortened input, a similar or a same text and does the process in reverse. This results in an expanded text.
It can be used with any text or notes that have the knowledge gaps. It is a great aid to any creative work
and it simply pin-points to data that may be of some relevance.
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Classify any two TXT documents, no training required - JAVA
...Instead, each TXT file is a category on its own, rather than an assigned category. In a way, this is similar to clustering but not really a clustering algorithm since there is some training involved. The summarizer from Classifier4J has been adjusted to accept two inputs (lets call them A and B). Then, the summarizer gets trained with A to summarize a document B, and vice versa. This extracts a relevant structure for both documents (and thus avoids the over-training) which are then compared using the Vector-Space analysis to give a range of belonging of one document to another (and thus avoids the shortage of information). ...
Auto summarization provides a concise summary for a document.
...My thesis Includes salton’s vector space model which divides the sentences into categories which can also be used for summarizing the contents in WebPages.
The summarizer initially breaks the entire document into sentences based on the separators.
The Second step is that the unnecessary words are removed from the document.
The document after removing the stop words is revised again for the unique words. Unique words are the one which have the same meaning or might be redundant in the document. ...
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Given a webpage, Summarizer tries to summarize the content such that all useful information is extracted in a small paragraph. This is something like what Google News uses to capture news summaries from sites. But this is not restricted to news sites.