How often do you find yourself in a situation where you start reading a content piece (News, Blogs, etc) based on a title just to find out that the content is nothing about the title. Unfortunately this happens to me a lot. I always thought that it would be wonderful if, similar to watching a trailer of the movie, or reading synopsys of a book, I could do the same for some of the online content. This will not only save me time but also help me understand the content much more as I start building context while reading the summary.
Two reasons why we run into this Situation
- The intent of a media publisher is different from a reader (This may not be true for all but in my opinion is applicable to most). Publishers often want to keep titles interesting to bait users in reading more and spend more time on their website.
- Authors are focused on providing the main body of the article and often do not go back to summarize.
Solution to solve the Issue
I believe that this can be easily solved by making few changes in how we read articles. As users discover content online before they start reading they can save the article in their library of online content (e.g. https://getsparks.io, in full disclosure this is the product I have been working on for quite some time). The program extracts content of the article from publishers and in the background runs through ML (Machine Learning) Algorithms based on NLP (Natural Language Processing) to process and analyze the content and produces a summary based on the article body.
As we process through content we discover other relevant information such as places, person, keywords mentioned in the article. There is much more users will be able to do while reading such as adding notes, highlighting specific text, schedule reminders etc. The product is currently in beta phase as we add more features and collect feedback. Please check out https://getsparks.io for a free account.
