V
Vagelis Hristidis
Researcher at University of California, Riverside
Publications - 162
Citations - 6770
Vagelis Hristidis is an academic researcher from University of California, Riverside. The author has contributed to research in topics: Ranking (information retrieval) & Ranking. The author has an hindex of 32, co-authored 155 publications receiving 6354 citations. Previous affiliations of Vagelis Hristidis include University of Miami & Florida International University.
Papers
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Book ChapterDOI
Discover: keyword search in relational databases
TL;DR: It is proved that DISCOVER finds without redundancy all relevant candidate networks, whose size can be data bound, by exploiting the structure of the schema and the selection of the optimal execution plan (way to reuse common subexpressions) is NP-complete.
Book ChapterDOI
Efficient IR-style keyword search over relational databases
TL;DR: This paper adapts IR-style document-relevance ranking strategies to the problem of processing free-form keyword queries over RDBMSs, and develops query-processing strategies that build on a crucial characteristic of IR- style keyword search: only the few most relevant matches are generally of interest.
Book ChapterDOI
Objectrank: authority-based keyword search in databases
TL;DR: The ObjectRank system applies authority-based ranking to keyword search in databases modeled as labeled graphs and precompute single keyword ObjectRanks and combine them during run time to address the issue of authority ranking with respect to the given keywords.
Proceedings ArticleDOI
Keyword Search on Spatial Databases
TL;DR: This work presents an efficient method to answer top-k spatial keyword queries using an indexing structure called IR2-Tree (Information Retrieval R-Tree) which combines an R- Tree with superimposed text signatures.
Proceedings ArticleDOI
PREFER: a system for the efficient execution of multi-parametric ranked queries
TL;DR: The results indicate that the proposed algorithms are superior in performance compared to other approaches, both in preprocessing (preparation of materialized views) as well as execution time.