Abstract
The availability of vast amounts of diverse information related to a broad topic makes it difficult and time-consuming for users to find and digest the right information regarding various low-level topics within the broader space. Current approaches to addressing these challenges include providing curated topical pages, relevant query refinement suggestions, list of subtopics, etc. However, these approaches do not scale and offer inadequate support for sensemaking. This disclosure describes automated techniques that extract information from online information sources by using a query related to a high-level topic to recursively formulate additional queries for subtopics to construct a hierarchical set of topics related to the broad query. The results can be utilized to provide a user interface using the hierarchical topic levels which can make it faster and easier for users to understand and navigate information regarding a high-level topic.
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Recommended Citation
Jain, Alankar; Leszczuk, William M; Iyer, Sitaram; Sharifi, Mehrbod; and Altiok, Seher Aylin, "Sensemaking for Broad Topics via Automated Extraction and Recursive Search", Technical Disclosure Commons, (November 18, 2020)
https://www.tdcommons.org/dpubs_series/3785