Our work on Publication Venue Recommendation based on Paper Abstract has been accepted for presentation at the IEEE International Conference on Tools with Artificial Intelligence (ICTAI) which will be held at November in Cyprus.
In this paper, we propose three methods for proposing a suitable publication venue for an ongoing research work, for which only the title and abstract are available. Two methods are based on Latent Dirichlet Allocation, whereas the best performing one is based on comparing n-grams language profiles.
A contribution of our proposal, which we evaluated experimentally on a dataset of 58,000 papers, is that we use only title and abstract. No full-text is needed for obtaining meaningful recommendations, nor authorship or references, as in previous works. Hence, the recommender can be used in the early stages of the authoring process. Moreover, it may greatly simplify the building and maintenance of the knowledge base.