https://github.com/shubham0204/text2summary-android
A library for Text Summarization on Android applications.
https://github.com/shubham0204/text2summary-android
android android-development android-library kotlin kotlin-android kotlin-library text-processing text-summarization tf-idf-algorithm
Last synced: 19 days ago
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A library for Text Summarization on Android applications.
- Host: GitHub
- URL: https://github.com/shubham0204/text2summary-android
- Owner: shubham0204
- License: apache-2.0
- Created: 2020-04-15T02:01:00.000Z (over 5 years ago)
- Default Branch: master
- Last Pushed: 2023-11-07T04:47:04.000Z (almost 2 years ago)
- Last Synced: 2025-01-17T14:47:18.112Z (9 months ago)
- Topics: android, android-development, android-library, kotlin, kotlin-android, kotlin-library, text-processing, text-summarization, tf-idf-algorithm
- Language: Kotlin
- Homepage: https://medium.com/@equipintelligence/introducing-text2summary-text-summarization-on-android-674b62419019
- Size: 9.63 MB
- Stars: 26
- Watchers: 2
- Forks: 5
- Open Issues: 1
-
Metadata Files:
- Readme: README.md
- License: LICENSE.txt
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README
# Text2Summary - Text Summarization with TFIDF in Kotlin
[](https://jitpack.io/#shubham0204/Text2Summary-Android)
[](https://forthebadge.com)
Text2Summary API uses on-device methods to perform text summarization on Android applications. It uses extractive text summarization
to give you the most important sentences from a given text.
You may [read the story of Text2Summary on Medium](https://medium.com/@equipintelligence/introducing-text2summary-text-summarization-on-android-674b62419019).
* [Installation](#installation)
* [Usage](#usage)
* [More on Text2Summary](#more-on-text2summary)
* [Contribute](#contribute)
## Installation
For the latest fat JAR, see [Releases](https://github.com/shubham0204/Text2Summary-Android/releases).
## Usage
The text which needs to be summarized has to be a `String` object. Then,
use `Text2Summary.summarize()` method to generate the summary.
`Text2Summary.summarize()` is a suspend function and hence it should be called within a `CoroutineContext`.
```kotlin
runBlocking {
var summary = Text2Summary.summarize(someLongText, compressionRate = 0.7)
}
```
The number `0.7` is referred as the compression factor. Meaning, given a text of 10 sentences, a summary of 7 sentences will be
produced. This number must lie in the interval `( 0 , 1 )`.
You may extract text from a file and then pass it to Text2Summary,
```kotlin
val bufferedReader: BufferedReader = File( "poems.txt" ).bufferedReader()
val text = bufferedReader.use{ it.readText() }
val summary = Text2Summary.summarize( text , 0.7 )
```
The `summarizeAsync()` method internally calls the `summarize()` method itself wrapped in a `AsyncTask`.
## More on Text2Summary
Text2Summary uses the TF-IDF algorithm for extractive text summarization. Note, this is not abstractive text summarization which
use neural networks like the Seq2Seq model. As TensorFlow Lite does not support fully the conversion of `Embedding` and `LSTM`
layers, we need to use the TF-IDF algorithm.
1. The `text` which is given to `TextSummary.summarize()` is broken down into sentences. These sentences are further brought down
to words ( tokens ).
2. Using TF-IDF algorithm, a TF-IDF score is calculated for each word.
3. Next, we take the sum of such scores for all words present in the sentence.
4. Finally, we take the top N highest scores. The corresponding sentences hold most of the information present in the text. These
sentences are then concatenated and returned as the summary.
## Contribute
If you are facing any issues, [open an issue](https://github.com/shubham0204/Text2Summary/issues) on the repository.