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Code for "Hierarchical Dirichlet-Hawkes process: generative model and inference algorithm", WWW 2017

============================================================================= hdhp : Simulation and inference for the hierarchical Dirichlet-Hawkes process

This is a Python implementation of the hierarchical Dirichlet-Hawkes process, that includes both the generation and the inference algorithm. For more details about this process and an application on Stack Overflow data, please see the pre-print publication on arXiv_.

.. _arXiv: https://arxiv.org/abs/1610.05775

To cite this work, please use

::

Mavroforakis, C., Valera, I. and Rodriguez, M.G., Modeling the Dynamics of Online Learning Activity. Proceedings of the 26th International Conference on World Wide Web. ACM, 2017.

Main Features

  • Generative model for the hierarchical Dirichlet-Hawkes process

  • Inference algorithm based on sequential Monte-Carlo

  • Multi-threaded

  • Arbitrary choice of vocabulary

  • Plotting capabilities

Installation

You can install the hdhp package by executing the following command in a terminal.

::

pip install hdhp

Documentation

For instructions on how to use the package, consult its documentation__.

__ http://hdhpypy.readthedocs.io/en/latest/

Examples

You can find an example of how to use this package in the Jupyter notebooks under the directory examples.

Note that the code is distributed under the Open Source Initiative (ISC) license. For the exact terms of distribution, see the LICENSE_.

.. _LICENSE: ./LICENSE

::

Copyright (c) 2016, hdhp contributors Charalampos Mavroforakis [email protected], Isabel Valera [email protected], Manuel Gomez-Rodriguez [email protected]