메뉴 건너뛰기




Volumn 2015-May, Issue , 2015, Pages 1729-1744

Mining quality phrases from massive text corpora

Author keywords

[No Author keywords available]

Indexed keywords

EFFICIENCY; METADATA; SEMANTICS;

EID: 84952656631     PISSN: 07308078     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/2723372.2751523     Document Type: Conference Paper
Times cited : (199)

References (41)
  • 1
    • 84866865020 scopus 로고    scopus 로고
    • University of Surrey participation in trec8: Weirdness indexing for logical document extrapolation and retrieval (wilder)
    • Gaithersburg, Maryland
    • K. Ahmad, L. Gillam, and L. Tostevin. University of surrey participation in trec8: Weirdness indexing for logical document extrapolation and retrieval (wilder). In The Eighth Text REtrieval Conference (TREC-8), Gaithersburg, Maryland.
    • The Eighth Text REtrieval Conference (TREC-8)
    • Ahmad, K.1    Gillam, L.2    Tostevin, L.3
  • 2
    • 0033466276 scopus 로고    scopus 로고
    • Knowledge discovery in documents by extracting frequent word sequences
    • H. Ahonen. Knowledge discovery in documents by extracting frequent word sequences. Library Trends, 48(1), 1999.
    • (1999) Library Trends , vol.48 , Issue.1
    • Ahonen, H.1
  • 3
    • 85162377681 scopus 로고    scopus 로고
    • Comparative analysis of viterbi training and maximum likelihood estimation for hmms
    • A. Allahverdyan and A. Galstyan. Comparative analysis of viterbi training and maximum likelihood estimation for hmms. In NIPS, pages 1674-1682, 2011.
    • (2011) NIPS , pp. 1674-1682
    • Allahverdyan, A.1    Galstyan, A.2
  • 5
    • 84859240198 scopus 로고    scopus 로고
    • Interesting-phrase mining for ad-hoc text analytics
    • S. Bedathur, K. Berberich, J. Dittrich, N. Mamoulis, and G. Weikum. Interesting-phrase mining for ad-hoc text analytics. VLDB, 3(1-2):1348-1357, 2010.
    • (2010) VLDB , vol.3 , Issue.1-2 , pp. 1348-1357
    • Bedathur, S.1    Berberich, K.2    Dittrich, J.3    Mamoulis, N.4    Weikum, G.5
  • 7
    • 80053425907 scopus 로고    scopus 로고
    • Phrasal segmentation models for statistical machine translation
    • G. Blackwood, A. De Gispert, and W. Byrne. Phrasal segmentation models for statistical machine translation. In COLING, 2008.
    • (2008) COLING
    • Blackwood, G.1    De Gispert, A.2    Byrne, W.3
  • 8
    • 0035478854 scopus 로고    scopus 로고
    • Random forests
    • L. Breiman. Random forests. Machine learning, 45(1):5-32, 2001.
    • (2001) Machine Learning , vol.45 , Issue.1 , pp. 5-32
    • Breiman, L.1
  • 10
    • 0006702490 scopus 로고
    • Extracting noun phrases from large-scale texts: A hybrid approach and its automatic evaluation
    • K.-h. Chen and H.-H. Chen. Extracting noun phrases from large-scale texts: A hybrid approach and its automatic evaluation. In ACL, 1994.
    • (1994) ACL
    • Chen K.-.1    Chen, H.-H.2
  • 11
    • 0014797273 scopus 로고
    • A relational model for large shared data banks
    • E. F. Codd. A Relational Model for Large Shared Data Banks. Communications of The ACM, 13:377-387, 1970.
    • (1970) Communications of the ACM , vol.13 , pp. 377-387
    • Codd, E.F.1
  • 12
    • 84959911781 scopus 로고    scopus 로고
    • Automatic construction and ranking of topical keyphrases on collections of short documents
    • M. Danilevsky, C. Wang, N. Desai, X. Ren, J. Guo, and J. Han. Automatic construction and ranking of topical keyphrases on collections of short documents. In SDM, 2014.
    • (2014) SDM
    • Danilevsky, M.1    Wang, C.2    Desai, N.3    Ren, X.4    Guo, J.5    Han, J.6
  • 13
    • 84859898690 scopus 로고    scopus 로고
    • A nonparametric method for extraction of candidate phrasal terms
    • P. Deane. A nonparametric method for extraction of candidate phrasal terms. In ACL, 2005.
    • (2005) ACL
    • Deane, P.1
  • 14
    • 84859985749 scopus 로고    scopus 로고
    • Automatic evaluation method for machine translation using noun-phrase chunking
    • H. Echizen-ya and K. Araki. Automatic evaluation method for machine translation using noun-phrase chunking. In ACL, 2010.
    • (2010) ACL
    • Echizen-Ya, H.1    Araki, K.2
  • 15
    • 84938053135 scopus 로고    scopus 로고
    • Scalable topical phrase mining from text corpora
    • Aug.
    • A. El-Kishky, Y. Song, C. Wang, C. R. Voss, and J. Han. Scalable topical phrase mining from text corpora. VLDB, 8(3), Aug. 2015.
    • (2015) VLDB , vol.8 , Issue.3
    • El-Kishky, A.1    Song, Y.2    Wang, C.3    Voss, C.R.4    Han, J.5
  • 16
    • 78650633610 scopus 로고    scopus 로고
    • Automatic recognition of multi-word terms: The c-value/nc-value method
    • K. Frantzi, S. Ananiadou, and H. Mima. Automatic recognition of multi-word terms:. the c-value/nc-value method. JODL, 3(2):115-130, 2000.
    • (2000) JODL , vol.3 , Issue.2 , pp. 115-130
    • Frantzi, K.1    Ananiadou, S.2    Mima, H.3
  • 17
    • 84957603491 scopus 로고    scopus 로고
    • Top-k interesting phrase mining in ad-hoc collections using sequence pattern indexing
    • C. Gao and S. Michel. Top-k interesting phrase mining in ad-hoc collections using sequence pattern indexing. In EDBT, 2012.
    • (2012) EDBT
    • Gao, C.1    Michel, S.2
  • 18
    • 0037796798 scopus 로고
    • Lexis as a linguistic level
    • M. A. Halliday. Lexis as a linguistic level. In memory of JR Firth, pages 148-162, 1966.
    • (1966) Memory of JR Firth , pp. 148-162
    • Halliday, M.A.1
  • 19
    • 80052752148 scopus 로고    scopus 로고
    • Conundrums in unsupervised keyphrase extraction: Making sense of the state-of-theart
    • K. S. Hasan and V. Ng. Conundrums in unsupervised keyphrase extraction: making sense of the state-of-theart. In COLING, 2010.
    • (2010) COLING
    • Hasan, K.S.1    Ng, V.2
  • 21
    • 71049177089 scopus 로고    scopus 로고
    • Memetracking and the dynamics of the news cycle
    • J. Leskovec, L. Backstrom, and J. Kleinberg. Memetracking and the dynamics of the news cycle. In KDD, KDD '09, pages 497-506, 2009.
    • (2009) KDD, KDD '09 , pp. 497-506
    • Leskovec, J.1    Backstrom, L.2    Kleinberg, J.3
  • 22
    • 84880798303 scopus 로고    scopus 로고
    • Learning to classify texts using positive and unlabeled data
    • X. Li and B. Liu. Learning to classify texts using positive and unlabeled data. In IJCAI, volume 3, pages 587-592, 2003.
    • (2003) IJCAI , vol.3 , pp. 587-592
    • Li, X.1    Liu, B.2
  • 23
    • 80052130523 scopus 로고    scopus 로고
    • Unsupervised query segmentation using clickthrough for information retrieval
    • Y. Li, B.-J. P. Hsu, C. Zhai, and K. Wang. Unsupervised query segmentation using clickthrough for information retrieval. In SIGIR, 2011.
    • (2011) SIGIR
    • Li, Y.1    Hsu, P.B.-J.2    Zhai, C.3    Wang, K.4
  • 25
    • 80053274459 scopus 로고    scopus 로고
    • Non-projective dependency parsing using spanning tree algorithms
    • R. McDonald, F. Pereira, K. Ribarov, and J. Hajič. Non-projective dependency parsing using spanning tree algorithms. In EMNLP, 2005.
    • (2005) EMNLP
    • McDonald, R.1    Pereira, F.2    Ribarov, K.3    Hajič, J.4
  • 26
    • 85114317854 scopus 로고    scopus 로고
    • Textrank: Bringing order into texts
    • R. Mihalcea and P. Tarau. Textrank: Bringing order into texts. In ACL, 2004.
    • (2004) ACL
    • Mihalcea, R.1    Tarau, P.2
  • 27
    • 84898956512 scopus 로고    scopus 로고
    • Distributed representations of words and phrases and their compositionality
    • T. Mikolov, I. Sutskever, K. Chen, G. S. Corrado, and J. Dean. Distributed representations of words and phrases and their compositionality. In NIPS, pages 3111-3119, 2013.
    • (2013) NIPS , pp. 3111-3119
    • Mikolov, T.1    Sutskever, I.2    Chen, K.3    Corrado, G.S.4    Dean, J.5
  • 28
    • 84957535519 scopus 로고    scopus 로고
    • Fast mining of interesting phrases from subsets of text corpora
    • D. P, A. Dey, and D. Majumdar. Fast mining of interesting phrases from subsets of text corpora. In EDBT, 2014.
    • (2014) EDBT
    • Dey, D.P.A.1    Majumdar, D.2
  • 30
    • 33645109468 scopus 로고    scopus 로고
    • Automatic glossary extraction: Beyond terminology identification
    • Y. Park, R. J. Byrd, and B. K. Boguraev. Automatic glossary extraction: beyond terminology identification. In COLING, 2002.
    • (2002) COLING
    • Park, Y.1    Byrd, R.J.2    Boguraev, B.K.3
  • 31
    • 84899004090 scopus 로고    scopus 로고
    • The use of classifiers in sequential inference
    • V. Punyakanok and D. Roth. The use of classifiers in sequential inference. In NIPS, 2001.
    • (2001) NIPS
    • Punyakanok, V.1    Roth, D.2
  • 32
    • 80053405922 scopus 로고    scopus 로고
    • Multiword expressions in the wild? The mwetoolkit comes in handy
    • C. Ramisch, A. Villavicencio, and C. Boitet. Multiword expressions in the wild? the mwetoolkit comes in handy. In COLING, pages 57-60, 2010.
    • (2010) COLING , pp. 57-60
    • Ramisch, C.1    Villavicencio, A.2    Boitet, C.3
  • 35
    • 0001076101 scopus 로고    scopus 로고
    • A stochastic finite-state word-segmentation algorithm for Chinese
    • R. Sproat, W. Gale, C. Shih, and N. Chang. A stochastic finite-state word-segmentation algorithm for chinese. Computational linguistics, 22(3):377-404, 1996.
    • (1996) Computational Linguistics , vol.22 , Issue.3 , pp. 377-404
    • Sproat, R.1    Gale, W.2    Shih, C.3    Chang, N.4
  • 36
    • 57349162751 scopus 로고    scopus 로고
    • Unsupervised query segmentation using generative language models and wikipedia
    • B. Tan and F. Peng. Unsupervised query segmentation using generative language models and wikipedia. In WWW, 2008.
    • (2008) WWW
    • Tan, B.1    Peng, F.2
  • 37
    • 85109864082 scopus 로고    scopus 로고
    • Introduction to the conll-2000 shared task: Chunking
    • E. F. Tjong Kim Sang and S. Buchholz. Introduction to the conll-2000 shared task: Chunking. In CONLL, 2000.
    • (2000) CONLL
    • Tjong Kim Sang, E.F.1    Buchholz, S.2
  • 39
    • 85119985187 scopus 로고    scopus 로고
    • A unified statistical model for the identification of english basenp
    • E. Xun, C. Huang, and M. Zhou. A unified statistical model for the identification of english basenp. In ACL, 2000.
    • (2000) ACL
    • Xun, E.1    Huang, C.2    Zhou, M.3
  • 40
    • 77957599476 scopus 로고    scopus 로고
    • Topic cube: Topic modeling for OLAP on multidimensional text databases
    • D. Zhang, C. Zhai, and J. Han. Topic Cube: Topic Modeling for OLAP on Multidimensional Text Databases. In SDM, pages 1123-1134, 2009.
    • (2009) SDM , pp. 1123-1134
    • Zhang, D.1    Zhai, C.2    Han, J.3
  • 41
    • 84957551067 scopus 로고    scopus 로고
    • A comparative evaluation of term recognition algorithms
    • Z. Zhang, J. Iria, C. A. Brewster, and F. Ciravegna. A comparative evaluation of term recognition algorithms. LREC, 2008.
    • (2008) LREC
    • Zhang, Z.1    Iria, J.2    Brewster, C.A.3    Ciravegna, F.4


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.