Vagelis Hristidis
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.
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Index Terms
- Authority-based keyword search in databases
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Reviews
Donald Harris Kraft
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 demonstration Web site is available. The system allows a user to input a set of keywords as a query, with optional Boolean operators. The user can also input a global object-rank importance parameter, a damping factor, and a specificity metric (inverse object rank). The database is an available set of documents that can be accessed on the Web. Hristidis et al. note that a query keyword provides a set of documents with that keyword, and then the database graph can be traversed to provide a keyword-specific ranking. Moreover, one can calibrate the specificity metric (inverse object rank) and quality metric (global object rank). Finally, the paper offers an ontology graph, based on domain knowledge, to expand the search?only the inheritance of attributes, the "isa" relationship, is considered. The paper provides an interesting approach that merits further consideration and testing. Online Computing Reviews Service
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