Search Results for "scoring"

X For You Feed Algorithm is the open-sourced core recommendation system that powers the For You feed on X (the social network formerly known as Twitter), and it represents one of the first times a major social platform has published production-level ranking code for public review and experimentation. The repository contains the full pipeline that ingests user engagement and content candidate data, processes it through retrieval, hydration, filtering, scoring, and selection layers, and ultimately ranks posts to show what appears in a user’s feed. At its heart, the system uses a transformer-based model adapted from xAI’s Grok architecture to predict probabilities for various user actions (such as likes, replies, reposts, clicks, and negative signals), then combines those into a weighted final score that drives ranking.

A collection of algorithms for querying a set of documents and returning the ones most relevant to the query. The most common use case for these algorithms is, as you might have guessed, to create search engines.

...The algorithm uses features such as sentence length, keyword frequency, and position within the document to determine which sentences are most relevant. By combining these features with a simple scoring mechanism, it produces summaries that are both readable and informative. Originally inspired by research and earlier implementations, textteaser provides a lightweight solution for summarization without requiring heavy machine learning models. It is particularly useful for developers, researchers, or content platforms seeking a simple, rule-based approach to article summarization.

...This software is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY. In case you use the package in your work, we do appreciate a citation to a DSS publication. Citation: Yadav et al. (2014), Quantitative scoring of differential drug sensitivity for individually optimized anticancer therapies. Scientific Reports 4, 5193; DOI:10.1038/srep05193 Please visit the link below for details

...In case you use the package in your work, we do appreciate a citation to the publications below. Citation: Yadav B, Peddinti G, Pemovska T, Khan SA, Szwajda A, Tang J, Wennerberg K and Aittokallio T. From drug response profiling to target addiction scoring in cancer cell models. (Submitted)