%0 Journal Article %1 Kroll2023 %A Kroll, Hermann %A Pirklbauer, Jan %A Kalo, Jan-Christoph %A Kunz, Morris %A Ruthmann, Johannes %A Balke, Wolf-Tilo %D 2023 %J International Journal on Digital Libraries %K digital_libraries knowledge_graphs myown %R 10.1007/s00799-023-00356-3 %T A discovery system for narrative query graphs: entity-interaction-aware document retrieval %U https://doi.org/10.1007/s00799-023-00356-3 %X Finding relevant publications in the scientific domain can be quite tedious: Accessing large-scale document collections often means to formulate an initial keyword-based query followed by many refinements to retrieve a sufficiently complete, yet manageable set of documents to satisfy one's information need. Since keyword-based search limits researchers to formulating their information needs as a set of unconnected keywords, retrieval systems try to guess each user's intent. In contrast, distilling short narratives of the searchers' information needs into simple, yet precise entity-interaction graph patterns provides all information needed for a precise search. As an additional benefit, such graph patterns may also feature variable nodes to flexibly allow for different substitutions of entities taking a specified role. An evaluation over the PubMed document collection quantifies the gains in precision for our novel entity-interaction-aware search. Moreover, we perform expert interviews and a questionnaire to verify the usefulness of our system in practice. This paper extends our previous work by giving a comprehensive overview about the discovery system to realize narrative query graph retrieval.

@article{Kroll2023, abstract = {Finding relevant publications in the scientific domain can be quite tedious: Accessing large-scale document collections often means to formulate an initial keyword-based query followed by many refinements to retrieve a sufficiently complete, yet manageable set of documents to satisfy one's information need. Since keyword-based search limits researchers to formulating their information needs as a set of unconnected keywords, retrieval systems try to guess each user's intent. In contrast, distilling short narratives of the searchers' information needs into simple, yet precise entity-interaction graph patterns provides all information needed for a precise search. As an additional benefit, such graph patterns may also feature variable nodes to flexibly allow for different substitutions of entities taking a specified role. An evaluation over the PubMed document collection quantifies the gains in precision for our novel entity-interaction-aware search. Moreover, we perform expert interviews and a questionnaire to verify the usefulness of our system in practice. This paper extends our previous work by giving a comprehensive overview about the discovery system to realize narrative query graph retrieval.}, added-at = {2024-02-06T08:09:08.000+0100}, author = {Kroll, Hermann and Pirklbauer, Jan and Kalo, Jan-Christoph and Kunz, Morris and Ruthmann, Johannes and Balke, Wolf-Tilo}, biburl = {https://www.bibsonomy.org/bibtex/2b11e7b67c0f66cd4cfecf1b914ce4345/balke}, day = 24, doi = {10.1007/s00799-023-00356-3}, interhash = {082f3c5500fc92b4faf27da3714ff4bb}, intrahash = {b11e7b67c0f66cd4cfecf1b914ce4345}, issn = {1432-1300}, journal = {International Journal on Digital Libraries}, keywords = {digital_libraries knowledge_graphs myown}, month = apr, timestamp = {2024-02-06T08:09:08.000+0100}, title = {A discovery system for narrative query graphs: entity-interaction-aware document retrieval}, url = {https://doi.org/10.1007/s00799-023-00356-3}, year = 2023 }