2015/09/07 by Fredrik Carlsen, Carlsen, Fredrik Nygård
Computer Science · #Digital Libraries (cs.DL) #FOS: Computer and information sciences #Information Retrieval (cs.IR) #Information Retrieval and Search Behavior #Recommender Systems and Techniques #Web Data Mining and Analysis
paper · pdf · doi:10.48550/arxiv.1509.02207
openalex publication_date 2015/09/07 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
As the volume of electronically available information grows, relevant items become harder to find. This work presents an approach to personalizing search results in scientific publication databases. This work focuses on re-ranking search results from existing search engines like Solr or ElasticSearch. This work also includes the development of Obelix, a new recommendation system used to re-rank search results. The project was proposed and performed at CERN, using the scientific publications available on the CERN Document Server (CDS). This work experiments with re-ranking using offline and online evaluation of users and documents in CDS. The experiments conclude that the personalized search result outperform both latest first and word similarity in terms of click position in the search result for global search in CDS.