Please use this identifier to cite or link to this item: https://idr.nitk.ac.in/jspui/handle/123456789/7333
Title: An unsupervised method for attribute identification from a natural language query
Authors: Bhaskaran, R.
Chandavarkar, B.R.
Issue Date: 2018
Citation: Advances in Intelligent Systems and Computing, 2018, Vol.518, , pp.543-549
Abstract: Identifying which attributes the user querying is an important step in providing a Natural language (NL) search interface to a relational database. In this paper, we discuss an unsupervised approach for identifying the target database attributes from natural language (NL) query. This is a knowledge base-driven method which can be adopted into any domain with very little effort. Initially, we created a knowledge base using background information about the database domain. Then used a probabilistic algorithm to calculate the semantic dependency between different nodes in the knowledge base. When processing the query, this dependency score will be used to resolve the target attribute. � Springer Nature Singapore Pte Ltd. 2018.
URI: http://idr.nitk.ac.in/jspui/handle/123456789/7333
Appears in Collections:2. Conference Papers

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