Publication Venue Recommendation Based on Paper Abstract
| Autor: | Eric Medvet, Alberto Bartoli, Giulio Piccinin |
|---|---|
| Přispěvatelé: | IEEE, Medvet, Eric, Bartoli, Alberto, Piccinin, Giulio |
| Jazyk: | angličtina |
| Rok vydání: | 2014 |
| Předmět: |
Matching (statistics)
Recommending systems Information retrieval Recommending systems Latent Dirichlet Allocation n-grams Computer science business.industry Process (engineering) media_common.quotation_subject Recommender system Latent Dirichlet allocation Field (computer science) symbols.namesake Knowledge base symbols Quality (business) Metric (unit) Latent Dirichlet Allocation business n-grams media_common |
| Zdroj: | ICTAI |
| Popis: | We consider the problem of matching the topics of a scientific paper with those of possible publication venues for that paper. While every researcher knows the few top-level venues for his specific fields of interest, a venue recommendation system may be a significant aid when starting to explore a new research field. We propose a venue recommendation system which requires only title and abstract, differently from previous works which require full-text and reference list: hence, our system can be used even in the early stages of the authoring process and greatly simplifies the building and maintenance of the knowledge base necessary for generating meaningful recommendations. We assessed our proposal using a standard metric on a dataset of more than 58000 papers: the results show that our method provides recommendations whose quality is aligned with previous works, while requiring much less information from both the paper and the knowledge base. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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