Keyword searching and browsing in databases using BANKS

Gaurav Bhalotia, Arvind Hulgeri, Charuta Nakhe, Soumen Chakrabarti, S. Sudarshan
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引用次数: 1070

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.
使用BANKS对数据库进行关键词搜索和浏览
随着Web的发展,需要在没有模式或查询语言详细知识的情况下访问在线数据库的用户数量迅速增加;即使是为非专家设计的相对简单的查询语言对他们来说也太复杂了。我们描述了BANKS,这是一个能够在关系数据库中进行基于关键字的搜索,以及数据和模式浏览的系统。BANKS使用户能够以一种简单的方式提取信息,而无需了解模式或编写复杂查询。用户可以通过输入几个关键字、跟随超链接并与显示结果上的控件进行交互来获取信息。BANKS将元组建模为图中的节点,通过由外键和其他关系引起的链接连接。查询的答案建模为根树,连接与查询中单个关键字匹配的元组。答案的排名使用了临近度的概念以及基于链接的节点声望的概念,类似于为Web搜索开发的技术。我们提出了一种高效的启发式算法来查找和排序查询结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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