Authors: Aditya Telang, Chengkai Li, Sharma Chakravarthy
Tags: 2009, conceptual modeling
The staples of information retrieval have been querying and search, respectively, for structured and unstructured repositories. Processing queries over known, structured repositories (e.g., Databases) has been well-understood, and search has become ubiquitous when it comes to unstructured repositories (e.g., Web). Furthermore, searching structured repositories has been explored to a limited extent. However, there is not much work in querying unstructured sources. We argue that querying unstructured sources is the next step in performing focused retrievals. This paper proposed a new approach to generate queries from search-like inputs for unstructured repositories. Instead of burdening the user with schema details, we believe that pre-discovered semantic information in the form of taxonomies, relationship of keywords based on context, and attribute & operator compatibility can be used to generate query skeletons. Furthermore, progressive feedback from users can be used to improve the accuracy of query skeletons generated.Read the full paper here: https://link.springer.com/chapter/10.1007/978-3-642-04840-1_16
