an effective path-aware approach for keyword search over data graphs

Keyword search is known as a user-friendly alternative for structured languages to retrieve information from graph-structured data. efficient retrieving of relevant answers to a keyword query and effective ranking of these answers according to their relevance are two main challenges in the keyword search over graph- structured data. in this paper, a novel scoring function is proposed, which utilizes both the textual and structural features of answers in order to produce a more accurate order of answers. in addition, a query processing algorithm is developed based on information spreading technique to enumerate answers in approximate order. this algorithm is further improved by allowing a skewed development toward more promising paths and enables a more efficient processing of keyword queries. performance evaluation through extensive experiments on a standard benchmark of three real- world datasets shows the effectiveness and efficiency of the proposed algorithms.