Welcome to IQP: Incremental Query Construction, a Probabilistic Approach
Databases enable users to precisely express their informational needs using structured queries. However, database query construction is a laborious and error-prone process, which cannot be performed well by novice users. Keyword search alleviates the usability problem at the price of query expressiveness. As keyword search algorithms do not differentiate the possible informational needs represented by a keyword query, even a theoretically optimal algorithm can, at best, rank the most frequent informational needs highest, while users with less frequent needs would not receive adequate results.
IQP is a novel approach to bridge the gap between the usability of keyword search and the expressiveness of database queries. IQP enables the user to start with an arbitrary keyword query and incrementally refine it into a structured query. IQP consists of three components: (1) a framework for incremental query construction, which requires only minimal user interaction and no a-priori schema knowledge; (2) a novel probabilistic model to assess the possible informational needs represented as a keyword query; (3) an algorithm to optimize the query construction process.Start IQP Applet
Example queries for IMDB
Example queries for Lyrics
The current IQP implementation interprets all keywords as attribute values. For example, an IMDB query can contain keywords from movie title, movie year, and plot text as well as actor, director or character names. Lyrics queries can include keywords from artist names as well as song or album titles. Further keyword interpretations e.g. schema terms and operator names are currently under construction. The dump of the IMDB database includes movies up to 2007.