The Sixteenth International Symposium on Intelligent Data Analysis (IDA 2017).
Archived – Please note this event series took place in the past and has been left here for reference purposes. View our full list of events to see what we have coming up or if there is a particular type of event you are interested in.
Date: 26-28 October 2017
Venue: London, UK
When the IDA Symposium series started in 1995, it focused on the problem of end-to-end intelligent support for data analysis. In 2010, the symposium re-focused to support papers that go beyond established technology and offer genuinely novel and game-changing ideas, whilst not always being as fully realized as papers submitted to other conferences.
The symposium seeks first look papers that might elsewhere be considered preliminary, but contain potentially high impact research. The IDA Symposium, which is A-ranked according to ERA, is open to all kinds of modeling and analysis methods, irrespective of discipline. It is expected to be an interdisciplinary meeting that seeks abstractions that cut across domains.
Our Senior Data Development Manager, Richard Skeggs will be presenting his paper at the conference:
Title: Federated Searching with Natural Language Interface to Database
Abstract: The concept of federated searching allows the user to search multiple data repositories for a requested search value from a single interface. This topic has been within the research field since the 1980`s. Mazur (1) defined federated searching as a global model which consisted of `n` local repositories. Most organisations whether they are in the public or private sector have more than one data repositories. The advent of internet search engines such as google have increased the expectations of users to be able to access data from anywhere within increasing shorter timelines. This has put pressure on organisations to be able to successfully implement a federated search engine. This paper proposes the use of Natural Language Interface to Databases along with the techniques employed by indexing engines to simplify the federated search. By implementing an index file, which allows quick access to data as a grammar file which defines the structure of the natural language statement, the paper discusses how this approach can reduce the complexity of NLIDB.
For more information on the conference, visit the IDA 2017 website.