Abstract
Vertical search engines are meant for answering a user's web query within a specific domain such as news, media, and academic web searching. One main difference between vertical and horizontal web searching is that in vertical web searching, unlike horizontal web searching, a subset of entire web is engaged. The chapter investigates the state-of-the-art in academic web searching and points out shortcomings in this particular domain. Lastly, the authors aimed to propose a summary-based recommender to respond to a user's query by retrieving and ranking them according to their similarity merits on the basis of papers' summaries. Results of the evaluations revealed the fact that the proposed framework has outperformed the state-of-the-art in different metrics such as unanimous ranks and F1 measures.
Reference33 articles.
1. Research-paper recommender systems: A literature survey.;J.Beel;International Journal on Digital Libraries,2015
2. Beel, J., Langer, S., Genzmehr, M., Gipp, B., Breitinger, C., & Nürnberger, A. (2013). Research paper recommender system evaluation: A quantitative literature survey. Proceedings of the International Workshop on Reproducibility and Replication in Recommender Systems Evaluation, RepSys ’13, 15–22.
3. Recommending scientific articles using citeulike
4. Bradshaw, S. (2003). Reference directed indexing: Redeeming relevance for subject search in citation indexes. Lecture Notes in Computer Science, 2769, 499–510.
5. Christopher, D. (2008). Introduction to information retrieval. Cambridge University Press.