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musque's Introduction

Event-specific Document Ranking through Multi-stage Query Expansion

Welcome to the GitHub repository for the paper titled 'Event-specific Document Ranking through Multi-stage Query Expansion using an Event Knowledge Graph'. This repository contains the implementation code for the MusQuE model and the created dataset Ms-Marco-Event.

Dataset: Ms-Marco-Event

Ms-Marco-Event dataset is created based on the MS-MARCO dataset and the EventKG event knowledge graph. This dataset contains event-related queries from Ms-Marco dataset. Please refer to the main [MS-MARCO dataset] (https://microsoft.github.io/msmarco/Datasets.html) for more detailed information and specific dataset guidelines.

MusQuE

MusQuE is an approach for event-specific document ranking through Multi-stage Query Expansion. We provide the implementation of MusQuE for training and evaluation.

License

Distributed under the MIT License. See LICENSE for more information.

musque's People

Contributors

saraabdollahi avatar

Stargazers

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Watchers

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musque's Issues

Request for "Event-specific Document Ranking through Multi-stage Query Expansion using an Event Knowledge Graph" PDF

Dear saraabdollahi,

I am Lean, and I am highly interested in your work on the "MusQuE" GitHub repository, particularly regarding the "Event-specific Document Ranking through Multi-stage Query Expansion using an Event Knowledge Graph."

In my academic research, I have identified that literature in this area is crucial to my work. I would like to request access to the relevant PDF document to gain a more in-depth understanding of your contributions to this project.

If there are alternative ways to access this information, please let me know. I would greatly appreciate your assistance.

Request for Additional Dataset Details and Clarification on train_iteration Function Error

Hello sara,

I hope this message finds you well. I am reaching out to inquire about the dataset used in your project hosted on GitHub. I find your work extremely insightful and beneficial, but I am encountering some difficulties understanding the specifics of your dataset and the train_iteration function.

Could you please provide more details on the dataset? Specifically, I am interested in understanding what each parameter represents. Additionally, while running the train_iteration function, I encountered an error stating "loss of this epoch is: tensor(nan, device='cuda:0')". This issue is preventing me from progressing further in my project, and I was hoping you could offer some guidance or insights into what might be causing this error.

Furthermore, if you have any supporting documentation, such as a PDF file or model diagrams, that could offer more in-depth insights into your work, it would be immensely helpful. Such resources would greatly enhance my understanding and ability to effectively utilize your project.

If it is convenient for you, could you kindly send the relevant files or documentation to my email at [email protected]? I would be profoundly grateful for any help or information you can provide.

Thank you very much for your time and assistance. I look forward to your response.

Best regards,
Lean

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