Where to Submit? Helping Researchers to Choose the Right Venue

@inproceedings{Kobs2020WhereTS,
  title={Where to Submit? Helping Researchers to Choose the Right Venue},
  author={Konstantin Kobs and Tobias Koopmann and Albin Zehe and David Fernes and Philipp Krop and Andreas Hotho},
  booktitle={Findings},
  year={2020}
}
Whenever researchers write a paper, the same question occurs: “Where to submit?” In this work, we introduce WTS, an open and interpretable NLP system that recommends conferences and journals to researchers based on the title, abstract, and/or keywords of a given paper. We adapt the TextCNN architecture and automatically analyze its predictions using the Integrated Gradients method to highlight words and phrases that led to the recommendation of a scientific venue. We train and test our method… 
View on ACL
aclanthology.org
4 Citations
Highly Influential Citations
1
Background Citations
3
Methods Citations
1
Results Citations
1

Figures and Tables from this paper

4 Citations

Towards Explainable Scientific Venue Recommendations

An unsophisticated method is proposed that enhances the interpretability of recommendations through non-negative matrix factorization based topic models and surprisingly can obtain competitive recommendation performance while using simpler learning methods.

DeSCoVeR: Debiased Semantic Context Prior for Venue Recommendation

A novel semantic context prior-based venue recommendation system that uses only the title and the abstract of a paper that outperforms the state-of-the-art methods.

Explainable Natural Language Processing

  • Anders Søgaard
  • Computer Science
    Synthesis Lectures on Human Language Technologies
  • 2021

GraphConfRec: A Graph Neural Network-Based Conference Recommender System

GraphConfRec, a conference recommender system which combines SciGraph and graph neural networks, is proposed, to infer suggestions based not only on title and abstract, but also on coauthorship and citation relationships.

References

SHOWING 1-10 OF 20 REFERENCES

Jane: suggesting journals, finding experts

Jane (Journal/Author Name Estimator) is a freely available web-based application that, on the basis of a sample text, can suggest journals and experts who have published similar articles.

Building a Conference Recommender System Based on SciGraph and WikiCFP

This paper discusses how the SciGraph dataset can be utilized to build a conference recommendation system, yielding a recall@10 of up to 0.665, and a MAP of 0.540, generating recommendations based on authors, abstracts, and keywords.

Construction of the Literature Graph in Semantic Scholar

This paper reduces literature graph construction into familiar NLP tasks, point out research challenges due to differences from standard formulations of these tasks, and report empirical results for each task.

BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

A new language representation model, BERT, designed to pre-train deep bidirectional representations from unlabeled text by jointly conditioning on both left and right context in all layers, which can be fine-tuned with just one additional output layer to create state-of-the-art models for a wide range of tasks.

Conferences versus journals in computer science

Results from the analysis show that CS, as a discipline, values conferences as a publication venue more highly than any other academic field of study.

Adam: A Method for Stochastic Optimization

This work introduces Adam, an algorithm for first-order gradient-based optimization of stochastic objective functions, based on adaptive estimates of lower-order moments, and provides a regret bound on the convergence rate that is comparable to the best known results under the online convex optimization framework.

Was ist eine Professur fuer Kuenstliche Intelligenz?

A view that is often followed when appointing professors for AI at German and international universities is presented, in order to help to establish a guideline with internationally accepted measures and thus make the public debate more informed.

On Term Selection for Query Expansion

A quantitative argument is sketches a quantitative argument which suggests that the two purposes of relevance feedback system and retrieval purposes require different weighting formulae.

Convolutional Neural Networks for Sentence Classification

The CNN models discussed herein improve upon the state of the art on 4 out of 7 tasks, which include sentiment analysis and question classification, and are proposed to allow for the use of both task-specific and static vectors.

Scikit-learn: Machine Learning in Python

Scikit-learn is a Python module integrating a wide range of state-of-the-art machine learning algorithms for medium-scale supervised and unsupervised problems. This package focuses on bringing…