{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T06:43:26Z","timestamp":1740120206016,"version":"3.37.3"},"reference-count":31,"publisher":"World Scientific Pub Co Pte Ltd","issue":"04","funder":[{"DOI":"10.13039\/501100012166","name":"National Key R & D Program of China","doi-asserted-by":"crossref","award":["2018YFC0809800"],"award-info":[{"award-number":["2018YFC0809800"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Int. J. Soft. Eng. Knowl. Eng."],"published-print":{"date-parts":[[2023,4]]},"abstract":"<jats:p> Identifying notable tuples in a web table is of great help for table understanding and table summarization. However, existing document-internal feature-based methods are inappropriate for identifying notable tuples in web tables. Additionally, for the web table describing multiple concepts, the notability evaluation of a tuple needs to take into account multiple entities as well as their importance in this tuple. In this paper, we investigate the task of identifying notable tuples in a multi-concept web table and propose a framework that includes three tasks: (1) identify multiple entity columns and their importance weights by building a column correlation graph based on types and relationships in the table; (2) obtain fine-grained entity notability scores based on entity link graph and provide solution for entity link failure and entity domain neglection; and (3) evaluate tuple notability by a weighted sum of notability scores of all entities in the tuple. Comprehensive evaluation of our approach is based on real-world web tables. The results demonstrate that our approach outperforms the state-of-the-art baselines by 4.6% on the precision of detecting multiple entity columns and by 12.5% on the metric normalized discounted cumulative gain (NDCG) of evaluating entity notability. <\/jats:p>","DOI":"10.1142\/s0218194023500080","type":"journal-article","created":{"date-parts":[[2023,2,24]],"date-time":"2023-02-24T13:09:09Z","timestamp":1677244149000},"page":"575-602","source":"Crossref","is-referenced-by-count":0,"title":["Identifying Notable Tuples in Multi-Concept Web Tables"],"prefix":"10.1142","volume":"33","author":[{"given":"Yihai","family":"Xi","sequence":"first","affiliation":[{"name":"School of Computer and Information Technology, Beijing Jiaotong University, Beijing 100044, P. R. China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ning","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Computer and Information Technology, Beijing Jiaotong University, Beijing 100044, P. R. China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"219","published-online":{"date-parts":[[2023,4,18]]},"reference":[{"key":"S0218194023500080BIB001","first-page":"181","volume-title":"ACM Conf. Management of Data","author":"Singh M.","year":"2012"},{"key":"S0218194023500080BIB002","first-page":"231","volume-title":"IEEE Int. Conf. Data Engineering","author":"Nguyen T. T.","year":"2015"},{"key":"S0218194023500080BIB003","doi-asserted-by":"crossref","first-page":"969","DOI":"10.4149\/cai_2018_4_969","volume":"37","author":"Wang N.","year":"2018","journal-title":"Comput. 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