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> Note: MatchZoo-py is developed under Python 3.6.
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Welcome! MatchZoo is a community project that aims to work for a wide range of NLP and IR tasks such as Question Answering, Information Retrieval, Paraphrase identification etc. Your experience and what you can contribute are important to the project's success.
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Welcome! MatchZoo-py is a community project that aims to work for a wide range of NLP and IR tasks such as Question Answering, Information Retrieval, Paraphrase identification etc. Your experience and what you can contribute are important to the project's success.
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Discussion
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----------
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If you've run into behavior in MatchZoo you don't understand, or you're having trouble working out a good way to apply it to your code, or you've found a bug or would like a feature it doesn't have, we want to hear from you!
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If you've run into behavior in MatchZoo-py you don't understand, or you're having trouble working out a good way to apply it to your code, or you've found a bug or would like a feature it doesn't have, we want to hear from you!
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Our main forum for discussion is the project's [GitHub issue tracker](https://github.com/NTMC-Community/MatchZoo-py/issues). This is the right place to start a discussion of any of the above or most any other topic concerning the project.
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For less formal discussion we have a chat room on WeChat (mostly Chinese speakers). MatchZoo core developers are almost always present; feel free to find us there and we're happy to chat. Please add *YQ-Cai1198593462* as your WeChat friend, she will invite you to join the chat room.
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For less formal discussion we have a chat room on WeChat (mostly Chinese speakers). MatchZoo-py core developers are almost always present; feel free to find us there and we're happy to chat. Please add *YQ-Cai1198593462* as your WeChat friend, she will invite you to join the chat room.
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First Time Contributors
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-----------------------
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MatchZoo appreciates your contribution! If you are interested in helping improve MatchZoo, there are several ways to get started:
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MatchZoo-py appreciates your contribution! If you are interested in helping improve MatchZoo-py, there are several ways to get started:
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* Work on [new models](https://github.com/NTMC-Community/awaresome-neural-models-for-semantic-match).
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* Work on [tutorials](https://github.com/NTMC-Community/MatchZoo-py/tree/master/tutorials).
@@ -27,19 +27,19 @@ MatchZoo appreciates your contribution! If you are interested in helping improve
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Submitting Changes
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------------------
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Even more excellent than a good bug report is a fix for a bug, or the implementation of a much-needed new model.
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Even more excellent than a good bug report is a fix for a bug, or the implementation of a much-needed new model.
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(*) We'd love to have your contributions.
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(*) If your new feature will be a lot of work, we recommend talking to us early -- see below.
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We use the usual GitHub pull-request flow, which may be familiar to you if you've contributed to other projects on GitHub -- see below.
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We use the usual GitHub pull-request flow, which may be familiar to you if you've contributed to other projects on GitHub -- see below.
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Anyone interested in MatchZoo may review your code. One of the MatchZoo core developers will merge your pull request when they think it's ready.
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Anyone interested in MatchZoo-py may review your code. One of the MatchZoo-py core developers will merge your pull request when they think it's ready.
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For every pull request, we aim to promptly either merge it or say why it's not yet ready; if you go a few days without a reply, please feel
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free to ping the thread by adding a new comment.
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For a list of MatchZoo core developers, see [README](https://github.com/NTMC-Community/MatchZoo-py/blob/master/README.md).
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For a list of MatchZoo-py core developers, see [README](https://github.com/NTMC-Community/MatchZoo-py/blob/master/README.md).
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Contributing Flow
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------------------
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Your PR will be merged if:
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- Funcitonally benefit for the project.
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- Passed Countinuous Integration (all unit tests, integration tests and [PEP8](https://www.python.org/dev/peps/pep-0008/) check passed).
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- Test coverage didn't decreased, we use [pytest](https://docs.pytest.org/en/latest/).
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- With proper docstrings, see codebase as examples.
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- With type hints, see [typing](https://docs.python.org/3/library/typing.html).
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- All reviewers approved your changes.
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- Funcitonally benefit for the project.
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- Passed Countinuous Integration (all unit tests, integration tests and [PEP8](https://www.python.org/dev/peps/pep-0008/) check passed).
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- Test coverage didn't decreased, we use [pytest](https://docs.pytest.org/en/latest/).
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- With proper docstrings, see codebase as examples.
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- With type hints, see [typing](https://docs.python.org/3/library/typing.html).
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- All reviewers approved your changes.
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**Thanks and let's improve MatchZoo together!**
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**Thanks and let's improve MatchZoo-py together!**
-[ConvKNRM](https://github.com/NTMC-Community/MatchZoo-py/tree/master/matchzoo/models/conv_knrm.py): this model is an implementation of <ahref="http://www.cs.cmu.edu/~zhuyund/papers/WSDM_2018_Dai.pdf">Convolutional neural networks for soft-matching n-grams in ad-hoc search</a>
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-[ESIM](https://github.com/NTMC-Community/MatchZoo-py/tree/master/matchzoo/models/esim.py): this model is an implementation of <ahref="https://arxiv.org/abs/1609.06038">Enhanced LSTM for Natural Language Inference</a>
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-[BiMPM](https://github.com/NTMC-Community/MatchZoo-py/tree/master/matchzoo/models/bimpm.py): this model is an implementation of <ahref="https://arxiv.org/abs/1702.03814">Bilateral Multi-Perspective Matching for Natural Language Sentences</a>
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- Models under development: <ahref="https://arxiv.org/abs/1602.06359">MatchPyramid</a>, <ahref="https://arxiv.org/abs/1604.04378">Match-SRNN</a>, <ahref="https://arxiv.org/abs/1710.05649">DeepRank</a>, <ahref="https://arxiv.org/abs/1801.01641">aNMM</a> ....
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-[MatchPyramid](https://github.com/NTMC-Community/MatchZoo-py/tree/master/matchzoo/models/match_pyramid.py): this model is an implementation of <ahref="https://arxiv.org/abs/1602.06359">Text Matching as Image Recognition</a>
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-[Match-SRNN](https://github.com/NTMC-Community/MatchZoo-py/tree/master/matchzoo/models/match_srnn.py): this model is an implementation of <ahref="https://arxiv.org/abs/1604.04378">Match-SRNN: Modeling the Recursive Matching Structure with Spatial RNN</a>
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-[aNMM](https://github.com/NTMC-Community/MatchZoo-py/tree/master/matchzoo/models/anmm.py): this model is an implementation of <ahref="https://arxiv.org/abs/1801.01641">aNMM: Ranking Short Answer Texts with Attention-Based Neural Matching Model</a>
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-[MV-LSTM](https://github.com/NTMC-Community/MatchZoo-py/tree/master/matchzoo/models/mvlstm.py): this model is an implementation of <ahref="https://arxiv.org/pdf/1511.08277.pdf">A Deep Architecture for Semantic Matching with Multiple Positional Sentence Representations</a>
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-[DIIN](https://github.com/NTMC-Community/MatchZoo-py/tree/master/matchzoo/models/diin.py): this model is an implementation of <ahref="https://arxiv.org/pdf/1709.04348.pdf">Natural Lanuguage Inference Over Interaction Space</a>
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-[HBMP](https://github.com/NTMC-Community/MatchZoo-py/tree/master/matchzoo/models/hbmp.py): this model is an implementation of <ahref="https://arxiv.org/pdf/1808.08762.pdf">Sentence Embeddings in NLI with Iterative Refinement Encoders</a>
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-[BERT](https://github.com/NTMC-Community/MatchZoo-py/tree/master/matchzoo/models/bert.py): this model is an implementation of <ahref="https://arxiv.org/abs/1810.04805">BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding</a>
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## Citation
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