{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,27]],"date-time":"2025-11-27T16:13:56Z","timestamp":1764260036479},"reference-count":17,"publisher":"Association for Computing Machinery (ACM)","issue":"12","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Proc. VLDB Endow."],"published-print":{"date-parts":[[2018,8]]},"abstract":"<jats:p>There exists an ever-growing set of data-centric systems that allow data scientists of varying skill levels to interactively manipulate, analyze and explore large structured data sets. However, there are currently not many systems that allow data scientists and novice users to interactively explore large unstructured text document collections from heterogeneous sources.<\/jats:p>\n          <jats:p>In this demo paper, we present a new system for interactive text summarization called Sherlock. The task of automatically producing textual summaries is an important step to understand a collection of multiple topic-related documents. It has many real-world applications in journalism, medicine, and many more. However, none of the existing summarization systems allow users to provide feedback at interactive speed. We therefore integrate a new approximate summarization model into Sherlock that can guarantee interactive speeds even for large text collections to keep the user engaged in the process.<\/jats:p>","DOI":"10.14778\/3229863.3236220","type":"journal-article","created":{"date-parts":[[2018,9,10]],"date-time":"2018-09-10T12:12:28Z","timestamp":1536581548000},"page":"1902-1905","source":"Crossref","is-referenced-by-count":9,"title":["Sherlock"],"prefix":"10.14778","volume":"11","author":[{"given":"Avinesh P. V.","family":"S.","sequence":"first","affiliation":[{"name":"TU Darmstadt, Germany"}]},{"given":"Benjamin","family":"H\u00e4ttasch","sequence":"additional","affiliation":[{"name":"TU Darmstadt, Germany"}]},{"given":"Orkan","family":"\u00d6zyurt","sequence":"additional","affiliation":[{"name":"TU Darmstadt, Germany"}]},{"given":"Carsten","family":"Binnig","sequence":"additional","affiliation":[{"name":"TU Darmstadt, Germany and Brown University"}]},{"given":"Christian M.","family":"Meyer","sequence":"additional","affiliation":[{"name":"TU Darmstadt, Germany"}]}],"member":"320","published-online":{"date-parts":[[2018,8]]},"reference":[{"key":"e_1_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/D15-1220"},{"key":"e_1_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1145\/2882903.2915245"},{"key":"e_1_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1145\/2939502.2939513"},{"key":"e_1_2_1_4_1","volume-title":"conference 2006 corpus. http:\/\/duc.nist.gov\/duc2006","year":"2018","unstructured":"Document understanding conference 2006 corpus. http:\/\/duc.nist.gov\/duc2006 . Accessed : 2018 -03-01. Document understanding conference 2006 corpus. http:\/\/duc.nist.gov\/duc2006. Accessed: 2018-03-01."},{"key":"e_1_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/D17-2004"},{"key":"e_1_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1145\/2449396.2449413"},{"key":"e_1_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1145\/2911451.2914682"},{"key":"e_1_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.14778\/2733004.2733064"},{"key":"e_1_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICDE.2014.6816674"},{"key":"e_1_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.1145\/1978942.1979444"},{"key":"e_1_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1038\/nn.3447"},{"key":"e_1_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1109\/TVCG.2014.44"},{"key":"e_1_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.1111\/cgf.12129"},{"key":"e_1_2_1_14_1","first-page":"1353","volume-title":"ACL","author":"Meyer P. V. S.","year":"2017","unstructured":"Avinesh P. V. S. and C. M. Meyer . Joint optimization of user-desired content in multi-document summaries by learning from user feedback . In ACL , pages 1353 -- 1363 . ACL, 2017 . Avinesh P. V. S. and C. M. Meyer. Joint optimization of user-desired content in multi-document summaries by learning from user feedback. In ACL, pages 1353--1363. ACL, 2017."},{"key":"e_1_2_1_15_1","first-page":"404","volume-title":"EMNLP","author":"Mihalcea R.","year":"2004","unstructured":"R. Mihalcea and P. Tarau . Textrank: Bringing order into texts . In EMNLP , pages 404 -- 411 . ACL, 2004 . R. Mihalcea and P. Tarau. Textrank: Bringing order into texts. In EMNLP, pages 404--411. ACL, 2004."},{"key":"e_1_2_1_16_1","volume-title":"http:\/\/www.paxata.com","year":"2018","unstructured":"Paxata. http:\/\/www.paxata.com , 2018 . Accessed : 2018-03-01. Paxata. http:\/\/www.paxata.com, 2018. Accessed: 2018-03-01."},{"key":"e_1_2_1_17_1","volume-title":"http:\/\/www.trifacta.com","year":"2018","unstructured":"Trifacta. http:\/\/www.trifacta.com , 2018 . Accessed : 2018-03-01. Trifacta. http:\/\/www.trifacta.com, 2018. Accessed: 2018-03-01."}],"container-title":["Proceedings of the VLDB Endowment"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.14778\/3229863.3236220","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,12,28]],"date-time":"2022-12-28T10:13:41Z","timestamp":1672222421000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.14778\/3229863.3236220"}},"subtitle":["a system for interactive summarization of large text collections"],"short-title":[],"issued":{"date-parts":[[2018,8]]},"references-count":17,"journal-issue":{"issue":"12","published-print":{"date-parts":[[2018,8]]}},"alternative-id":["10.14778\/3229863.3236220"],"URL":"https:\/\/doi.org\/10.14778\/3229863.3236220","relation":{},"ISSN":["2150-8097"],"issn-type":[{"value":"2150-8097","type":"print"}],"subject":[],"published":{"date-parts":[[2018,8]]}}}