Authors: Yong-Jin Han, Tae-Gil Noh, Seong-Bae Park, Se Young Park, Sang-Jo Lee
Venue: IUI '10: Proceedings of the 15th international conference on Intelligent user interfaces
Summary
This paper is about improving the use of natural language interfaces by converting them to a formal language acceptable to the system. While the authors in this paper are talking about a broader range of systems, this work is very similar to search engines such as Google. Essentially, when a user enters a query in natural language, like you would in Google, you are presented with a series of recognized keywords from your query. The user then reviews the system's interpretation of their query to make sure it makes sense. Since the query is now written purely in formal language the system understands, results are much more predictable and accurate.
Discussion
The concepts discussed in this paper are very similar to auto complete on Google searches. However, as seen in the image above, queries made through this system are configured to be very precise, and are probably more intended for knowledge base systems such as Watson. Ultimately it comes down to what sort of database you are searching. In this paper the authors are clearly searching a highly formatted database, where as Google has to search a database that looks more like a heap.
While this was a good idea for these systems, I don't feel like it was a particularly original or creative solution. Most computer scientists, if presented with this problem, would probably come to a similar solution on their own. Additionally, the methods employed by Google and Watson are clearly both excellent already, so to some extent this is recreating the wheel, and not really new research.
No comments:
Post a Comment