rahuljha / content-models Goto Github PK
View Code? Open in Web Editor NEWImplementation of probabilistic LDA style content models
Implementation of probabilistic LDA style content models
Relevant code for the following publication: Rahul Jha, Catherine Finegan-Dollak, Ben King, Reed Coke and Dragomir Radev. Content Models for Survey Generation: A Factoid-Based Evaluation. Annual Meeting of the Association for Computational Linguistics, 2015. ----- Python implementation for TopicSum and HitSum. TopicSum implementation is based on: http://www.mblondel.org/journal/2010/08/21/latent-dirichlet-allocation-in-python/ https://github.com/rebeccamason/codesample/tree/master/TopicSum HitSum code will need to be adapted to suit your needs, I have added comments wherever possible. ----- For any questions regarding this code, please email [email protected].
A declarative, efficient, and flexible JavaScript library for building user interfaces.
๐ Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. ๐๐๐
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google โค๏ธ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.