메뉴 건너뛰기




Volumn , Issue , 2016, Pages 1025-1028

Automatic Entity Recognition and Typing in Massive Text Corpora

Author keywords

entity recognition and typing; massive text corpora

Indexed keywords

ENTITY RECOGNITION; ENTITY RECOGNITION AND TYPING; MASSIVE TEXT CORPUS; NATURAL LANGUAGES TEXTS; NEWS ARTICLES; PRODUCT REVIEWS; SOCIAL MEDIA; TEXT CORPORA; TEXT DATA; USER-GENERATED;

EID: 85047801459     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/2872518.2891065     Document Type: Conference Paper
Times cited : (13)

References (49)
  • 1
    • 84859921107 scopus 로고    scopus 로고
    • A high-performance semi-supervised learning method for text chunking
    • R. K. Ando and T. Zhang. A high-performance semi-supervised learning method for text chunking. In ACL, 2005.
    • (2005) ACL
    • Ando, R.K.1    Zhang, T.2
  • 3
    • 0032632354 scopus 로고    scopus 로고
    • An algorithm that learns what's in a name
    • D. M. Bikel, R. Schwartz, and R. M. Weischedel. An algorithm that learns what's in a name. Machine learning, 34 (1-3): 211-231, 1999.
    • (1999) Machine learning , vol.34 , Issue.1-3 , pp. 211-231
    • Bikel, D.M.1    Schwartz, R.2    Weischedel, R.M.3
  • 5
    • 57149137628 scopus 로고    scopus 로고
    • Freebase: A collaboratively created graph database for structuring human knowledge
    • K. Bollacker, C. Evans, P. Paritosh, T. Sturge, and J. Taylor. Freebase: A collaboratively created graph database for structuring human knowledge. In SIGMOD, 2008.
    • (2008) SIGMOD
    • Bollacker, K.1    Evans, C.2    Paritosh, P.3    Sturge, T.4    Taylor, J.5
  • 7
    • 12244290581 scopus 로고    scopus 로고
    • Exploiting dictionaries in named entity extraction: combining semi-markov extraction processes and data integration methods
    • W. W. Cohen and S. Sarawagi. Exploiting dictionaries in named entity extraction: combining semi-markov extraction processes and data integration methods. In SIGKDD, 2004.
    • (2004) SIGKDD
    • Cohen, W.W.1    Sarawagi, S.2
  • 8
    • 85045072379 scopus 로고    scopus 로고
    • Ranking algorithms for named-entity extraction: Boosting and the voted perceptron
    • Association for Computational Linguistics
    • M. Collins. Ranking algorithms for named-entity extraction: Boosting and the voted perceptron. In Proceedings of the 40th Annual Meeting on Association for Computational Linguistics, pages 489-496. Association for Computational Linguistics, 2002.
    • (2002) Proceedings of the 40th Annual Meeting on Association for Computational Linguistics , pp. 489-496
    • Collins, M.1
  • 9
    • 85118972638 scopus 로고    scopus 로고
    • Language independent ner using a maximum entropy tagger
    • J. R. Curran and S. Clark. Language independent ner using a maximum entropy tagger. In HLT-NAACL, 2003.
    • (2003) HLT-NAACL
    • Curran, J.R.1    Clark, S.2
  • 10
    • 84858032933 scopus 로고    scopus 로고
    • Websets: Extracting sets of entities from the web using unsupervised information extraction
    • B. B. Dalvi, W. W. Cohen, and J. Callan. Websets: Extracting sets of entities from the web using unsupervised information extraction. In WSDM, 2012.
    • (2012) WSDM
    • Dalvi, B.B.1    Cohen, W.W.2    Callan, J.3
  • 11
    • 84905830200 scopus 로고    scopus 로고
    • Knowledge vault: A web-scale approach to probabilistic knowledge fusion
    • X. L. Dong, T. Strohmann, S. Sun, and W. Zhang. Knowledge vault: A web-scale approach to probabilistic knowledge fusion. In SIGKDD, 2014.
    • (2014) SIGKDD
    • Dong, X.L.1    Strohmann, T.2    Sun, S.3    Zhang, W.4
  • 14
    • 80053288463 scopus 로고    scopus 로고
    • Identifying relations for open information extraction
    • A. Fader, S. Soderland, and O. Etzioni. Identifying relations for open information extraction. In EMNLP, 2011.
    • (2011) EMNLP
    • Fader, A.1    Soderland, S.2    Etzioni, O.3
  • 15
    • 84859918687 scopus 로고    scopus 로고
    • Incorporating non-local information into information extraction systems by gibbs sampling
    • J. R. Finkel, T. Grenager, and C. Manning. Incorporating non-local information into information extraction systems by gibbs sampling. In ACL, 2005.
    • (2005) ACL
    • Finkel, J.R.1    Grenager, T.2    Manning, C.3
  • 16
    • 65449152689 scopus 로고    scopus 로고
    • Entity categorization over large document collections
    • V. Ganti, A. C. König, and R. Vernica. Entity categorization over large document collections. In SIGKDD, 2008.
    • (2008) SIGKDD
    • Ganti, V.1    König, A.C.2    Vernica, R.3
  • 17
    • 84900419025 scopus 로고    scopus 로고
    • Joint topic modeling for event summarization across news and social media streams
    • W. Gao, P. Li, and K. Darwish. Joint topic modeling for event summarization across news and social media streams. In CIKM, 2012.
    • (2012) CIKM
    • Gao, W.1    Li, P.2    Darwish, K.3
  • 19
    • 84907016550 scopus 로고    scopus 로고
    • Linking tweets to news: A framework to enrich short text data in social media
    • W. Guo, H. Li, Ji, and M. T. Diab. Linking tweets to news: A framework to enrich short text data in social media. In ACL, 2013.
    • (2013) ACL
    • Guo, W.1    Li, H.2    Ji3    Diab, M.T.4
  • 20
    • 85042915323 scopus 로고    scopus 로고
    • Improved pattern learning for bootstrapped entity extraction
    • S. Gupta and C. D. Manning. Improved pattern learning for bootstrapped entity extraction. In CONLL, 2014.
    • (2014) CONLL
    • Gupta, S.1    Manning, C.D.2
  • 21
    • 84862640224 scopus 로고    scopus 로고
    • Seisa: set expansion by iterative similarity aggregation
    • Y. He and D. Xin. Seisa: set expansion by iterative similarity aggregation. In WWW, 2011.
    • (2011) WWW
    • He, Y.1    Xin, D.2
  • 22
    • 85129802256 scopus 로고    scopus 로고
    • Inducing domain-specific semantic class taggers from (almost) nothing
    • R. Huang and E. Riló. Inducing domain-specific semantic class taggers from (almost) nothing. In ACL, 2010.
    • (2010) ACL
    • Huang, R.1    Riló, E.2
  • 23
    • 84859087795 scopus 로고    scopus 로고
    • Knowledge base population: Successful approaches and challenges
    • H. Ji and R. Grishman. Knowledge base population: Successful approaches and challenges. In ACL, 2011.
    • (2011) ACL
    • Ji, H.1    Grishman, R.2
  • 24
    • 84893368465 scopus 로고    scopus 로고
    • Joint extraction and labeling via graph propagation for dictionary construction
    • D. S. Kim, K. Verma, and P. Z. Yeh. Joint extraction and labeling via graph propagation for dictionary construction. In AAAI, 2013.
    • (2013) AAAI
    • Kim, D.S.1    Verma, K.2    Yeh, P.Z.3
  • 25
    • 80053280334 scopus 로고    scopus 로고
    • Class label enhancement via related instances
    • Z. Kozareva, K. Voevodski, and S.-H. Teng. Class label enhancement via related instances. In EMNLP, 2011.
    • (2011) EMNLP
    • Kozareva, Z.1    Voevodski, K.2    Teng, S.-H.3
  • 27
    • 84906932622 scopus 로고    scopus 로고
    • Incremental joint extraction of entity mentions and relations
    • Q. Li and H. Ji. Incremental joint extraction of entity mentions and relations. In ACL, 2014.
    • (2014) ACL
    • Li, Q.1    Ji, H.2
  • 28
    • 79960022996 scopus 로고    scopus 로고
    • Annotating and searching web tables using entities, types and relationships
    • G. Limaye, S. Sarawagi, and S. Chakrabarti. Annotating and searching web tables using entities, types and relationships. VLDB, 3 (1-2): 1338-1347, 2010.
    • (2010) VLDB , vol.3 , Issue.1-2 , pp. 1338-1347
    • Limaye, G.1    Sarawagi, S.2    Chakrabarti, S.3
  • 29
    • 85185398851 scopus 로고    scopus 로고
    • Phrase clustering for discriminative learning
    • D. Lin and X. Wu. Phrase clustering for discriminative learning. In ACL, 2009.
    • (2009) ACL
    • Lin, D.1    Wu, X.2
  • 30
    • 84911131962 scopus 로고    scopus 로고
    • Populating knowledge base with collective entity mentions: A graph-based approach
    • H. Lin, Y. Jia, Y. Wang, X. Jin, X. Li, and X. Cheng. Populating knowledge base with collective entity mentions: A graph-based approach. In ASONAM, 2014.
    • (2014) ASONAM
    • Lin, H.1    Jia, Y.2    Wang, Y.3    Jin, X.4    Li, X.5    Cheng, X.6
  • 31
    • 84876787835 scopus 로고    scopus 로고
    • No noun phrase left behind: detecting and typing unlinkable entities
    • T. Lin, O. Etzioni, et al. No noun phrase left behind: detecting and typing unlinkable entities. In EMNLP, 2012.
    • (2012) EMNLP
    • Lin, T.1    Etzioni, O.2
  • 33
    • 85114433408 scopus 로고    scopus 로고
    • Fine-grained entity recognition
    • X. Ling and D. S. Weld. Fine-grained entity recognition. In AAAI, 2012.
    • (2012) AAAI
    • Ling, X.1    Weld, D.S.2
  • 34
    • 84952656631 scopus 로고    scopus 로고
    • Mining quality phrases from massive text corpora
    • J. Liu, J. Shang, C. Wang, X. Ren, and J. Han. Mining quality phrases from massive text corpora. In SIGMOD, 2015.
    • (2015) SIGMOD
    • Liu, J.1    Shang, J.2    Wang, C.3    Ren, X.4    Han, J.5
  • 35
    • 0000747663 scopus 로고    scopus 로고
    • Maximum entropy markov models for information extraction and segmentation
    • A. McCallum, D. Freitag, and F. C. Pereira. Maximum entropy markov models for information extraction and segmentation. In ICML, volume 17, pages 591-598, 2000.
    • (2000) ICML , vol.17 , pp. 591-598
    • McCallum, A.1    Freitag, D.2    Pereira, F.C.3
  • 36
    • 8644248693 scopus 로고    scopus 로고
    • Entity extraction without language-specific resources
    • P. McNamee and J. Mayfield. Entity extraction without language-specific resources. In COLING, 2002.
    • (2002) COLING
    • McNamee, P.1    Mayfield, J.2
  • 37
    • 47749122510 scopus 로고    scopus 로고
    • A survey of named entity recognition and classification
    • D. Nadeau and S. Sekine. A survey of named entity recognition and classification. Lingvisticae Investigationes, 30 (1): 3-26, 2007.
    • (2007) Lingvisticae Investigationes , vol.30 , Issue.1 , pp. 3-26
    • Nadeau, D.1    Sekine, S.2
  • 38
    • 84906933410 scopus 로고    scopus 로고
    • Fine-grained semantic typing of emerging entities
    • N. Nakashole, T. Tylenda, and G. Weikum. Fine-grained semantic typing of emerging entities. In ACL, 2013.
    • (2013) ACL
    • Nakashole, N.1    Tylenda, T.2    Weikum, G.3
  • 39
    • 85136905861 scopus 로고    scopus 로고
    • Analyzing the Effiectiveness and applicability of co-training
    • K. Nigam and R. Ghani. Analyzing the Effiectiveness and applicability of co-training. In CIKM, 2000.
    • (2000) CIKM
    • Nigam, K.1    Ghani, R.2
  • 40
    • 84970915264 scopus 로고    scopus 로고
    • Design challenges and misconceptions in named entity recognition
    • L. Ratinov and D. Roth. Design challenges and misconceptions in named entity recognition. In ACL, 2009.
    • (2009) ACL
    • Ratinov, L.1    Roth, D.2
  • 41
    • 84954097569 scopus 로고    scopus 로고
    • Clustype: Effiective entity recognition and typing by relation phrase-based clustering
    • X. Ren, A. El-Kishky, C. Wang, F. Tao, C. R. Voss, and J. Han. Clustype: Effiective entity recognition and typing by relation phrase-based clustering. In SIGKDD, 2015.
    • (2015) SIGKDD
    • Ren, X.1    El-Kishky, A.2    Wang, C.3    Tao, F.4    Voss, C.R.5    Han, J.6
  • 42
    • 80053238545 scopus 로고    scopus 로고
    • Named entity recognition in tweets: An experimental study
    • A. Ritter, S. Clark, O. Etzioni, et al. Named entity recognition in tweets: An experimental study. In EMNLP, 2011.
    • (2011) EMNLP
    • Ritter, A.1    Clark, S.2    Etzioni, O.3
  • 43
    • 84970908874 scopus 로고    scopus 로고
    • Entity linking with a knowledge base: Issues, techniques, and solutions
    • W. Shen, J. Wang, and J. Han. Entity linking with a knowledge base: Issues, techniques, and solutions. TKDE, (99): 1-20, 2014.
    • (2014) TKDE , Issue.99 , pp. 1-20
    • Shen, W.1    Wang, J.2    Han, J.3
  • 44
    • 84996485765 scopus 로고    scopus 로고
    • A graph-based approach for ontology population with named entities
    • W. Shen, J. Wang, P. Luo, and M. Wang. A graph-based approach for ontology population with named entities. In CIKM, 2012.
    • (2012) CIKM
    • Shen, W.1    Wang, J.2    Luo, P.3    Wang, M.4
  • 45
    • 84877045207 scopus 로고    scopus 로고
    • Mining heterogeneous information networks: A structural analysis approach
    • Y. Sun and J. Han. Mining heterogeneous information networks: A structural analysis approach. SIGKDD Explorations, 14 (2): 20-28, 2013.
    • (2013) SIGKDD Explorations , vol.14 , Issue.2 , pp. 20-28
    • Sun, Y.1    Han, J.2
  • 46
    • 78549292887 scopus 로고    scopus 로고
    • A context pattern induction method for named entity extraction
    • P. P. Talukdar, T. Brants, M. Liberman, and F. Pereira. A context pattern induction method for named entity extraction. In CONLL, 2006.
    • (2006) CONLL
    • Talukdar, P.P.1    Brants, T.2    Liberman, M.3    Pereira, F.4
  • 47
    • 80053243816 scopus 로고    scopus 로고
    • Experiments in graph-based semi-supervised learning methods for class-instance acquisition
    • P. P. Talukdar and F. Pereira. Experiments in graph-based semi-supervised learning methods for class-instance acquisition. In ACL, 2010.
    • (2010) ACL
    • Talukdar, P.P.1    Pereira, F.2
  • 48
    • 80053495924 scopus 로고    scopus 로고
    • Word representations: A simple and general method for semi-supervised learning
    • J. Turian, L. Ratinov, and Y. Bengio. Word representations: A simple and general method for semi-supervised learning. In ACL, 2010.
    • (2010) ACL
    • Turian, J.1    Ratinov, L.2    Bengio, Y.3
  • 49
    • 38149056006 scopus 로고    scopus 로고
    • Unsupervised learning of generalized names
    • R. Yangarber, W. Lin, and R. Grishman. Unsupervised learning of generalized names. In COLING, 2002.
    • (2002) COLING
    • Yangarber, R.1    Lin, W.2    Grishman, R.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.