Millions of posts are created every day on ShareChat and Moj which makes timely and precise detection of Integrity Violating Content (IVC) crucial for ensuring the safety of our users and the integrity of our platform.
Improving profile search accuracy using ElasticSearch n-gram tokenizer
Elasticsearch is a distributed document store that stores data in an inverted index. An inverted index lists every unique word that appears in any document and identifies all of the documents each
How we brought down storage costs for the Ads platform: Part 1
We just went through different solutions that we could use for the problem we have on our hands. All of these are valid solutions that could be used for different levels of scale.
How we brought down storage for the Ads platform: Part 2
our code needs to compare the number of times a user has already seen an ad to the configured frequency in real-time and for that, we need storage of how many times a user has seen an ad. On the face of it.
A deep dive into ShareChat Progressive Web App (PWA)
Furthermore, we have extensively used the bundle analysis tool for webpack called Bundle Analyser, which enables us to visualize both uncompressed and gzipped size of webpack output files with an interactive zoomable tree-map.
Automatic Natural Language Generation (NLG) has had a long tradition in the Computational Linguistics community, but the recent advances in deep learning have given it a new impetus. Its importance in the modern world cannot be overstated.
Netflix Archaius provides a DynamoDB client library with a FixedDelayPollingScheduler, which basically polls the config in fixed intervals. This was integrated to fetch sync/async thresholds, ignored APIs and similar other configs.
With an intent to make all deployments fully CD-compatible, the Infra team at ShareChat started to experiment with Spinnaker and we are happy to share our journey with you.
Visual Search and Data Processing: ShareChat’s Battle against Plagiarism
For a query post, inverted indices give us the potential result candidates for ranking. We then retrieve the codebooks for candidates, and also quantize the query to construct its codebook, according to its sub-vectors.
At ShareChat, our CNN architecture is based on DenseNet1, or ‘dense convolutional network’. DenseNet has a feed-forward processing layer architecture, connecting each layer with every other layer.