초록 열기/닫기 버튼
The Relational ranking method applies authority-based ranking in relational dataset that can be modeled as graphs considering also their tuples’ values. Authority directions from tuples that contain the given keywords and transfer to their corresponding neighboring nodes in accordance with their values and semantic connections. From our previous work, ObjectRank extends to ValueRank that also takes into account the value of tuples in authority transfer flows. In a maked difference from ObjectRank, which only considers authority flows through relationships, it is only valid in the bibliographic databases e.g. DBLP dataset, ValueRank facilitates the estimation of importance for any databases, e.g. trading databases, etc. A relational keyword search paradigm Object Summary (denote as OS) is proposed recently, given a set of keywords, a group of Object Summaries as its query result. An OS is a multilevel-tree data structure, in which node (namely the tuple with keywords) is OS’s root node, and the surrounding nodes are the summary of all data on the graph. But, some of these trees have a very large in total number of tuples, size-l OSs are the OS snippets, have also been investigated using ValueRank.We evaluated the real bibliographical dataset and Microsoft business databases to verify of our proposed approach.
