Abstract
In this demo paper, we introduce a new search engine that supports Information Retrieval (IR) in a dynamic setting. A dynamic search engine distinguishes itself by handling rich interactions and temporal dependency among the queries in a session or for a task. The proposed search engine is called Dumpling, named after the development team's favorite food. It implements state-of-the-art dynamic search algorithms and provides: (i) a dynamic search toolkit by integrating the Query Change Retrieval Model (QCM) and the Win-win search algorithm; (ii) a user-friendly interface supporting side-by-side comparison of search results given by a state-of-the-art static search algorithm and the proposed dynamic search algorithms; (iii) and APIs for developers to apply the dynamic search algorithms to index and search over custom datasets. Dumpling is developed under the umbrella of a bigger project in the DARPA Memex program to crawl and search the dark web to support law enforcement and national security.
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