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ABSTRACT
Our system applies authority-based ranking to keyword search in databases modeled as labeled graphs. Three ranking factors are used: the relevance to the query, the specificity and the importance of the result. All factors are handled using authority-flow techniques that exploit the link-structure of the data graph, in contrast to traditional Information Retrieval. We address the performance challenges in computing the authority flows in databases by using precomputation and exploiting the database schema if present. We conducted user surveys and performance experiments on multiple real and synthetic datasets, to assess the semantic meaningfulness and performance of our system.
REFERENCES
Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.
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REVIEW
"Donald Harris Kraft : Reviewer"
Hristidis et al. extend the notion of ranking retrieved textual items from a database via Google's PageRank by giving authority to the "citing" papers and to the "citing" authors. The basic data structure is a labeled directed graph. A demonstrati
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