Development of an auto-summarization tool
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mechanical engineering crazy
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#1
15-08-2009, 06:13 PM


Development of an auto-summarization tool


Auto-summarization is a technique used to generate summaries of electronic documents. This has some applications like summarizing the search-engine results, providing briefs of big documents that do not have an abstract etc. There are two categories of summarizers, linguistic and statistical. Linguistic summarizers use knowledge about the languange (syntax/semantics/usage etc) to summarize a document. Statistical ones operate by finding the important sentences using statistical methods (like frequency of a particular word etc). Statistical summarizers normally do not use any linguistic information.
In this project and implimentation, an auto-summarization tool is developed using statistical techniques. The techniques involve finding the frequency of words, scoring the sentences, ranking the sentences etc. The summary is obtained by selecting a particular number of sentences (specified by the user) from the top of the list. It operates on a single document (but can be made to work on multiple documents by choosing proper algorithms for integration) and provides a summary of the document. The size of the summary can be specified by the user when invoking the tool. Pre-processing interfaces are there to handle the following document types: Plain Text, HTML, Word Document.

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gitarrenspieler
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#2
26-03-2011, 03:57 PM

I completed this project and implimentation in C#.net with all the modules and proper functioning based on Statistical Techniques. If anybody is interested in buying this project and implimentation at a very nominal price (only the price for my hard work), he/she may contact me at : pd07.kec@gmail.com, +919717950961 begin_of_the_skype_highlighting              +919717950961      end_of_the_skype_highlighting, pd007_kec@yahoo.com, facebookGitarrenspieler.
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seminar flower
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#3
14-09-2012, 04:42 PM

Development of an auto-summarization tool

Objective/Vision

This has some applications like summarizing the search-engine results, providing briefs of big documents that do not have an abstract etc. There are two categories of summarizers, linguistic and statistical. Linguistic summarizers use knowledge about the language to summarize a document. Statistical ones operate by finding the important sentences using statistical methods. Statistical summarizers normally do not use any linguistic information.

User of the System

A. Used to generate summaries of electronic documents
B. Using statistical techniques
C. techniques involve finding the frequency of words, scoring the sentences, ranking the sentences
D. To handle the document types like Plain Text, HTML, Word Document

Functional Requirements

i. Study about auto-summarizing techniques (some references are given in the references section of this document) and concentrate more on summarizers based on statistical techniques
ii. Collect the list of stop-words from an Internet site
iii. Come up with algorithms for the different functional components listed in the previous section. Some heuristic methods could be used to come up with modification of any existing algorithm
iv. Implement the pre-processor/sentence separator/word separator/word frequency calculator. These do not require much work on the algorithm side and existing algorithms will do fine.
v. Implement the scoring and ranking component
vi. Test it with some documents and tune the algorithms, if needed
vii. Bench-mark your tool against some tools available on the Internet
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