{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,28]],"date-time":"2025-10-28T00:32:15Z","timestamp":1761611535787},"publisher-location":"California","reference-count":0,"publisher":"International Joint Conferences on Artificial Intelligence Organization","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021,8]]},"abstract":"<jats:p>Exploring complex structured knowledge graphs (KGs) is challenging for non-experts as it requires knowledge of query languages and the underlying structure of the KGs. Keyword-based exploration is a convenient paradigm, and computing a group Steiner tree (GST) as an answer is a popular implementation. Recent studies suggested improving the cohesiveness of an answer where entities have small semantic distances from each other. However, how to efficiently compute such an answer is open. In this paper, to model cohesiveness in a generalized way, the quadratic group Steiner tree problem (QGSTP) is formulated where the cost function extends GST with quadratic terms representing semantic distances. For QGSTP we design a branch-and-bound best-first (B3F) algorithm where we exploit combinatorial methods to estimate lower bounds for costs. This exact algorithm shows practical performance on medium-sized KGs.<\/jats:p>","DOI":"10.24963\/ijcai.2021\/215","type":"proceedings-article","created":{"date-parts":[[2021,8,11]],"date-time":"2021-08-11T11:00:49Z","timestamp":1628679649000},"page":"1555-1562","source":"Crossref","is-referenced-by-count":7,"title":["Keyword-Based Knowledge Graph Exploration Based on Quadratic Group Steiner Trees"],"prefix":"10.24963","author":[{"given":"Yuxuan","family":"Shi","sequence":"first","affiliation":[{"name":"State Key Laboratory for Novel Software Technology, Nanjing University, China"},{"name":"Bosch Center for Artificial Intelligence, Renningen, Germany"}]},{"given":"Gong","family":"Cheng","sequence":"additional","affiliation":[{"name":"State Key Laboratory for Novel Software Technology, Nanjing University, China"}]},{"given":"Trung-Kien","family":"Tran","sequence":"additional","affiliation":[{"name":"Bosch Center for Artificial Intelligence, Renningen, Germany"}]},{"given":"Jie","family":"Tang","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Technology, Tsinghua University, China"}]},{"given":"Evgeny","family":"Kharlamov","sequence":"additional","affiliation":[{"name":"Bosch Center for Artificial Intelligence, Renningen, Germany"},{"name":"Department of Informatics, University of Oslo, Norway"}]}],"member":"10584","event":{"number":"30","sponsor":["International Joint Conferences on Artificial Intelligence Organization (IJCAI)"],"acronym":"IJCAI-2021","name":"Thirtieth International Joint Conference on Artificial Intelligence {IJCAI-21}","start":{"date-parts":[[2021,8,19]]},"theme":"Artificial Intelligence","location":"Montreal, Canada","end":{"date-parts":[[2021,8,27]]}},"container-title":["Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence"],"original-title":[],"deposited":{"date-parts":[[2021,8,11]],"date-time":"2021-08-11T11:02:03Z","timestamp":1628679723000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.ijcai.org\/proceedings\/2021\/215"}},"subtitle":[],"proceedings-subject":"Artificial Intelligence Research Articles","short-title":[],"issued":{"date-parts":[[2021,8]]},"references-count":0,"URL":"https:\/\/doi.org\/10.24963\/ijcai.2021\/215","relation":{},"subject":[],"published":{"date-parts":[[2021,8]]}}}