{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T04:30:45Z","timestamp":1750221045305,"version":"3.41.0"},"reference-count":7,"publisher":"Association for Computing Machinery (ACM)","issue":"1","license":[{"start":{"date-parts":[[2018,8,31]],"date-time":"2018-08-31T00:00:00Z","timestamp":1535673600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["SIGIR Forum"],"published-print":{"date-parts":[[2018,8,31]]},"abstract":"<jats:p>Past decade witnessed an explosive growth in the amount of unstructured data, especially in the public domain, mainly due to Web 2.0 and social media. This led to the creation of applications, called information extractors, that extract structured information from unstruc- tured data. The extracted information is stored in a Knowledge Base (KB). KB stores facts about entities like name, type and other attributes. My PhD thesis entitled 'Named Entity Extraction for Knowledgebase Enhancement' deals with information extraction on named entities with the purpose of enhancing a KB. The enhanced KB is in turn used by the information extraction task to refine the extraction process. Thus, KB provides structure and guidance to the extraction task, and gets enhanced by the results of the extraction task. Here we see that the tasks of entity extraction and KB enhancement are mutually dependent and mutually beneficial. Hence in my research I propose methods to enhance both the tasks, in an effort to build a strong and sound named entity extraction system. Named Entity Extraction, also known as Entity Linking (EL) in scientific literature, is the task of determining the identity of entities mentioned in text. EL helps automatic extraction of structured information about entities from unstructured data, which is stored in the KB. EL consists of Mention Detection and Entity Disambiguation. In my research, I propose methods to enhance mention detection, entity disambiguation and KB enhancement.<\/jats:p>","DOI":"10.1145\/3274784.3274807","type":"journal-article","created":{"date-parts":[[2018,9,4]],"date-time":"2018-09-04T12:37:30Z","timestamp":1536064650000},"page":"169-170","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":2,"title":["Named Entity Extraction for Knowledgebase Enhancement"],"prefix":"10.1145","volume":"52","author":[{"given":"Priya","family":"Radhakrishnan","sequence":"first","affiliation":[{"name":"IIIT Hyderabad, India"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2018,8,31]]},"reference":[{"key":"e_1_2_1_1_1","first-page":"71","volume-title":"Proceedings of the the 4th Workshop on Making Sense of Microposts co-located with the 23rd International World Wide Web Conference (WWW 2014","author":"Bansal R.","year":"2014"},{"key":"e_1_2_1_2_1","unstructured":"S. Gupta P. Radhakrishnan M. Gupta V. Varma and U. Gupta. Enhancing catego- rization of computer science research papers using knowledge bases. In Proceedings of the First Workshop on Knowledge Graphs and Semantics for Text Retrieval and Anal- ysis (KG4IR 2017) co-located with the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2017) Shinjuku Tokyo Japan August 11 2017. pages 38-42 2017.  S. Gupta P. Radhakrishnan M. Gupta V. Varma and U. Gupta. Enhancing catego- rization of computer science research papers using knowledge bases. In Proceedings of the First Workshop on Knowledge Graphs and Semantics for Text Retrieval and Anal- ysis (KG4IR 2017) co-located with the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2017) Shinjuku Tokyo Japan August 11 2017. pages 38-42 2017."},{"key":"e_1_2_1_3_1","first-page":"71","volume-title":"Proceedings of the the 4th Workshop on Making Sense of Microposts co-located with the 23rd International World Wide Web Conference (WWW 2014","author":"Bansal R.","year":"2014"},{"key":"e_1_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1145\/2600428.2609475"},{"key":"e_1_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/N18-1167"},{"volume-title":"Sneit: Salient named entity identification in tweets. Computacion y Sistemas, 21(4):665679","year":"2017","author":"Radhakrishnan P.","key":"e_1_2_1_6_1"},{"volume-title":"Proceedings of the Fifth Text Analysis Conference, TAC 2012","year":"2012","author":"Varma V.","key":"e_1_2_1_7_1"}],"container-title":["ACM SIGIR Forum"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3274784.3274807","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3274784.3274807","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T00:44:03Z","timestamp":1750207443000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3274784.3274807"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,8,31]]},"references-count":7,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2018,8,31]]}},"alternative-id":["10.1145\/3274784.3274807"],"URL":"https:\/\/doi.org\/10.1145\/3274784.3274807","relation":{},"ISSN":["0163-5840"],"issn-type":[{"type":"print","value":"0163-5840"}],"subject":[],"published":{"date-parts":[[2018,8,31]]},"assertion":[{"value":"2018-08-31","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}