Abstract | ||
---|---|---|
With the growth of the Web, there has been a rapid increase in the number of users who need to access online databases without having a detailed knowledge of the schema or of query languages; even relatively simple query languages designed for non-experts are too complicated for them. We describe BANKS, a system which enables keyword-based search on relational databases, together with data and schema browsing. BANKS enables users to extract information in a simple manner without any knowledge of the schema or any need for writing complex queries. A user can get information by typing a few keywords, following hyperlinks, and interacting with controls on the displayed results.BANKS models tuples as nodes in a graph, connected by links induced by foreign key and other relationships. Answers to a query are modeled as rooted trees connecting tuples that match individual keywords in the query. Answers are ranked using a notion of proximity coupled with a notion of prestige of nodes based on inlinks, similar to techniques developed for Web search. We present an efficient heuristic algorithm for finding and ranking query results. |
Year | Venue | Keywords |
---|---|---|
2002 | ICDE | query language,ranking query result,Web search,schema browsing,simple query language,BANKS models tuples,detailed knowledge,Keyword Searching,online databases,keyword-based search,complex query |
DocType | Citations | PageRank |
Conference | 233 | 14.86 |
References | Authors | |
0 | 2 |
Name | Order | Citations | PageRank |
---|---|---|---|
Arvind Hulgeri | 1 | 347 | 23.20 |
Charuta Nakhe | 2 | 308 | 19.69 |