AI News Summarizer - A Fully Automated Newspaper Summarizer Aims To Make Your Daily News Shorter By Utilizing AI.

Introduction

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What is SUMMARIZER ?

Summarizer is exclusive to $SMR holders. You won’t have to pay anything, just simply holding $SMR to read Summarizer contents. At any time, you decide to stop reading Summarizer, you can just sell your $SMR back to the market.

The Algorithm We Use

TextRank is an unsupervised algorithm for the automated summarization of texts that can also be used to obtain the most important keywords in a document. The algorithm applies a variation of PageRank over a graph constructed specifically for the task of summarization. This produces a ranking of the elements in the graph: the most important elements are the ones that better describe the text. This approach allows TextRank to build summaries without the need of a training corpus or labeling and allows the use of the algorithm with different languages.

For the task of automated summarization, TextRank models any document as a graph using sentences as nodes . A function to compute the similarity of sentences is needed to build edges in between. This function is used to weight the graph edges, the higher the similarity between sentences the more important the edge between them will be in the graph. In the domain of a Random Walker, as used frequently in PageRank , we can say that we are more likely to go from one sentence to another if they are very similar.

TextRank determines the relation of similarity between two sentences based on the content that both share. This overlap is calculated simply as the number of common lexical tokens between them, divided by the lenght of each to avoid promoting long sentences.

The function featured in the original algorithm can be formalized as:

• Definition 1. Given Si , Sj two sentences represented by a set of n words that in Si are represented as Si = wi , wi , …, wi . The similarity function for Si, Sj can be defined as:  The result of this process is a dense graph representing the document. From this graph, PageRank is used to compute the importance of each vertex. The most significative sentences are selected and presented in the same order as they appear in the document as the summary. These ideas are based in changing the way in which distances between sentences are computed to weight the edges of the graph used for PageRank. These similarity measures are orthogonal to the TextRank model, thus they can be easily integrated into the algorithm. We found some of these variations to produce significative improvements over the original algorithm.

• Definition 2. Given two sentences R, S, BM25 is defined as: where k and b are parameters. We used k = 1.2 and b = 0.75. avgDL is the average length of the sentences in our collection.

• This function definition implies that if a word appears in more than half the documents of the collection, it will have a negative value. Since this can cause problems in the next stage of the algorithm, we used the following correction formula: where ε takes a value between 0.5 and 0.30 and avgIDF is the average IDF for all terms. Other corrective strategies were also tested, setting ε = 0 and using simpler modifications of the classic IDF formula.

Evaluation

We tested LCS, Cosine Sim, BM25 and BM25+ as different ways to weight the edges for the TextRank graph. The best results were obtained using BM25 and BM25+ with the corrective formula shown in equation 3. We achieved.

Tokenomics

The distribution of SMR tokens will take place in 3 stages. Private sale for $0.008 per SMR. Join the whitelist to participate in private sales! The public sale will be made after the private sale at a rate of USD 0.01 per SMR. Launch on PancakeSwap, planned after private and public sale. Starting price: $0.012 per SMR. The project allocation is shown in the screenshot.

Token allocation is deployed to the Binance Smart Chain and we are integrating tokens with Summarizer via Web3. Our SMR token has passed the TechRate audit. The source code has also been published and tested by BSCScan.

Summarizer Roadmap

Summarizer was launched with in-depth development and research. The team also has a clear roadmap regarding Summarizer in the future. It is planned that Summarizer will be developed starting from implementing TextRank and designing the interface of Summarizer. Then the team will start developing a bots army and integrate the platform with the SMR Token so that it can be used by users. And the team will start developing the Summarizer application for the Android and iOS platforms, so that users can access Summarizer more easily through their smartphones. And then the team will carry out aggressive marketing and audits by TechRate to convince users that the code developed by the Summarizer team is really safe. Then finally the Summarizer team will list on CoinMarketCap, PancakeSwap, and several other exchanges.

Summarizer Team

• Brandon Thomas – Frontend Developer
• Chris Miller – Blockchain Developer
• Joy Stewart – Communications Manager
• Julie Hardin – Marketing Manager
• Mike Cook – Graphic Designer
• Robert Hoover – Backend Developer
• Steve Willis – Software Engineer

Conclusion

Sometimes online news platforms write news that is too long and not to the point, which makes readers have to spend more time to be able to read the news. Of course, this is for most people this is a bit annoying, especially for those who have limited time. And Summarizer is here as a platform that will sum up daily news, and make it shorter and easier for users to read. Summarizer works with bots that will crawl the web for news, summarize them, and then sort them into categories. In this way, Summarizer can deliver news stories to users in a shorter and easier to understand way and users can spend less time reading news from their various devices.

USEFUL LINKS :

• Newspaper website — https://summarizer.co/
• Telegram — https://t.me/SummarizerOfficial
• Medium — https://medium.com/@summarizer
• Twitter — https://twitter.com/SummarizerC
• Facebook — https://www.facebook.com/Summarizer-100158469034381/
• Reddit — https://www.reddit.com/user/Summarizer_Official
• Tokenomics website — https://token.summarizer.co/
• RoadMap website — https://token.summarizer.co/roadmap

AUTHOR :

• Bitcointalk Username : Ais08
• Bitcointalk Profile Link : https://bitcointalk.org/index.php?action=profile;u=894087
• Telegram Username : @Papacok
• BEP20 Wallet : 0x4354FC7Ced4a013618fcFD81FC74A261859E3246