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Survey on Ranking Functions in Keyword Search over Graph-Structured Data

Keyword search is known as an attractive alternative for structured query languages in querying over graph-structured data. A keyword query is expressed by a set of keywords and respond by a set of connected structures from the database, which totally or partially cover the queried keywords. These results show how the queried keywords are related in the database. Since there may be numerous results to a given query, a ranking function is essential to present top-k more relevant results to the user. The effectiveness of this function directly affected the effectiveness of the keyword search system. In this paper, we survey the proposed ranking functions in the context of keyword search. First, the proposed models for the results of a keyword query are discussed and a categorization of them is presented. Next, the effective factors in determining the relevance of results are examined. Then, various ranking functions for ordering the results of a query are described and categorized based on their main view in determining the semantic of the results. Finally, we present an analysis of these classes and discuss the evolution of new research strategies to resolve the issues associated with the ranking of results in the keyword search domain.