Automatic Article Summarizer Web Application
Can you summarize Lage text into small or meaningful text ?
Introduction
Text Summarization refers to the technique of shortening long pieces of text. The intention is to create a coherent and fluent summary having only the main points outlined in the document. It is the process of finding the most important information from a document to produce an abridged version with all the important ideas.
What are reason to use Text Summarizer ?
While summarization has been a field of study for decades, it has certainly grown in popularity in recent years.Earlier in 2014, data scientist Juan Manuel Torres Moreno published a full book on the subject titled “Automatic Text summarization” , where he provided 6 reasons why we need automatic text summarization tools:
- Summaries reduce reading time.
- When researching documents, summaries make the selection process easier.
- Automatic summarization improves the effectiveness of indexing.
- Automatic summarization algorithms are less biased than human summarizers.
- Personalized summaries are useful in question-answering systems as they provide personalized information.
- Using automatic or semi-automatic summarization systems enables commercial abstract services to increase the number of texts they are able to process.
Technology Use in this Application
Here in this application use of spaCy. It is a free, open-source library for advanced Natural Language Processing (NLP) in Python. spaCy provides the fastest and most accurate syntactic analysis of any NLP library released to date. It also offers access to larger word vectors that are easier to customize.
Methodology For This Application
Text summarization technique is divided into two approaches extractive and abstractive. But due to the limitation of natural language generation techniques in generating the abstractive summary generally extractive approach is used for summarization. For summarizing the text there is a need of structuring the text. First, in text summarization the text document is preprocessed . which means that removing stop words and punctuations.
Frequency table of words/Word Frequency Distribution — how many times each word appears in the document Score each sentence depending on the words it contains and the frequency table.
Maximum Word Frequency — Find the weighted frequency into the frequemcy table, Each word over most occuring word, Long sentence over short sentence.
Sentence Score and Ranking of Words in Each Sentence — Sentence Tokens, scoring every sentence based on number of words ,non stopwords in our word frequency table.
Build summary by joining every sentence above a certain sentence score.
How this Web Application works
Step 1) First decide what documents or article you need to summarize.
Step 2) After decided document paste data in given block
Step 3) Another option is possible to you have to enter selected document link in second block.
Step 4) You have passed step no. 2 & 3 then click on Summarize button and shows the summarize text.
Follow this 4 steps and then you have use this application very easily 😊.
Snapshot of web Application:
Conclusion:
Automatic Article Summarization has been shown to be useful for Natural Language Processing tasks such as Question Answering or Text Classification and other related fields of computer science such as Information retrieval and the access time for information searching will be improved.
Video of Application: Click Here
Web Application: Click Here
Download Android App: Click Here
Co-author : Jay Doshi
Guide : Priyanka Patel(Asst. Professor, KDPIT, CSPIT, CHARUSAT)
