Resilient ML

Data is the modern oil of the blockchain economy. ResilientML Semantic Reservoirs will bring a vast collection of carefully crafted semantic and linguistically tailored datasets curated by experts in Natural Language Processing for utilization directly in machine learning methods and sentiment models running in the Ocean environment and available through the Ocean marketplace via the ResilientML NLP data app.

Full Proposal

https://port.oceanprotocol.com/t/resilientml-python-analytics-suite-on-streamlit-io-and-data-sets-extension-and-expansion/935

Grant Deliverables

1. Continue to extend, develop and further curate our initial development of a Crypto specific Natural Language Processing Data Suite – this includes specifically continuing to expand the three data sets TASPEL-27, PASCOR-89, INVPEN-41.

2. Extend and deploy the online Analytics App dashboard that will show in real time the status of the Real News Crypto datasets TASPEL-27, PASCOR-89, INVPEN-41.

Specifically we will be adding additional analytics tools to demonstrate to the user:

• Word clouds (searchable by topic, news source, author or date range)
• Sentiment signals (to be implement in propriety sentiment entropy signals – positive, negative, neutral signals)
• Spectral heat-map diagrams for document-document spectra.

3. Develop fourth data set in the ResilientML suite of FaaS focussed on sentiment signals decomposed into polarities (positive, negative, neutral) by crypto news topic. The dataset expansion will span the additional following components:

• Web3.0 coins: Filecoin, BitTorrent, Stacks, The Graph, Basic Attention Token, Siacoin, Helium, Arweave;
• Layer1 coins (Solana);
• DeFi coins (Terra, PancakeSwap, Maker, THORChain, Serum);
• Metaverse/Gaming/NFT coins (Enjin, Axie Infinity, Red Fox Labs);
• Stablecoins (USDC, BUSD), and additional news sources:
• NewsBTC;
• Bitcoinist;
• Blocknomi;
• Coinspeaker. Specifically, in addition to the post-processed tokens, and the text-noise-free sentences, we will also provide parsimonious spectral features extracted from the articles via matrix factorisation approaches.

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