Title :
Venue Recommendation: Submitting Your Paper with Style
Author :
Zaihan Yang ; Davison, Brian D.
Author_Institution :
Dept. of Comput. Sci. & Eng., Lehigh Univ., Bethlehem, PA, USA
Abstract :
One of the principal goals for most research scientists is to publish. There are many thousands of publications: journals, conferences, workshops, and more, covering different topics and requiring different writing formats. However, when a researcher that is new to a certain research domain finishes the work, it is sometimes difficult to find a proper place to submit the paper. To solve this problem, we provide a collaborative-filtering-based recommendation system that can provide venue recommendations to researchers. In particular, we consider both topic and writing-style information, and differentiate the contributions of different kinds of neighboring papers to make such recommendations. Experiments based on real-world data from ACM and Cite Seer digital libraries demonstrate that our approach can provide effective recommendations.
Keywords :
collaborative filtering; digital libraries; publishing; recommender systems; ACM; CiteSeer digital libraries; collaborative-filtering-based recommendation system; conferences; journals; publications; venue recommendation; venue recommendations; workshops; writing formats; writing-style information; Feature extraction; Optimization; Publishing; Recommender systems; Syntactics; Vectors; Writing; collaborative-filtering; features; recommendation;
Conference_Titel :
Machine Learning and Applications (ICMLA), 2012 11th International Conference on
Conference_Location :
Boca Raton, FL
Print_ISBN :
978-1-4673-4651-1
DOI :
10.1109/ICMLA.2012.127