Skip to main content
Disciplines
Automotive Business IT + Informatics Construction + Real Estate Electrical Engineering + Electronics Energy + Sustainability Insurance + Risk Finance + Banking Management + Leadership Marketing + Sales Mechanical Engineering + Materials
Events
DE
EN
Books
Journals
Topic Page
Marketing
Start single access now
Access for companies
EXTENDED SEARCH
Log in
Top
World Wide Web
Published in: World Wide Web 1/2019

24-01-2018

Answering unique topic queries with dynamic threshold

Authors: Huixin Ma, Zhihui Yang, Yinan Jing, Zhenying He, X. Sean Wang

Published in: World Wide Web | Issue 1/2019

Log in

Activate our intelligent search to find suitable subject content or patents.

search-config
loading …

Abstract

Queries with threshold are common when dealing with unstructured data such as text corpus. It often requires several exploring attempts for users to achieve final results. In this work, we propose an automatic sampling method for threshold determination without any interaction with users, in which two optimizing algorithms are introduced to reach the lower-bound time complexity in each sampling trial. We evaluate our methods using several experiments and demonstrate the effectiveness of it, which can be an enormously powerful tool for ordinary users.
previous article An index structure supporting rule activation in pervasive applications
next article Attention based hierarchical LSTM network for context-aware microblog sentiment classification

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

inform now
Literature
1.
Bentley, J.: Programming pearls: algorithm design techniques. Commun. ACM 27(9), 865–873 (1984)CrossRef
2.
Bentley, J.: Programming pearls: perspective on performance. Commun. ACM 27(9), 1087–1092 (1984)CrossRef
3.
Blei, D. M., Ng, A. Y., Jordan, M. I.: Latent dirichlet allocation. J. Mach. Learn. Res. 3, 993–1022 (2003)MATH
4.
Cetintemel, U., Cherniack, M., DeBrabant, J., Diao, Y., Dimitriadou, K., Kalinin, A., Papaemmanouil, O., Zdonik, S. B.: Query steering for interactive data exploration. In: CIDR (2013)
5.
Cheng, R., Kalashnikov, D. V., Prabhakar, S.: Querying imprecise data in moving object environments. IEEE TKDE 16(9), 1112–1127 (2004)
6.
Diao, Y., Dimitriadou, K., Li, Z., Liu, W., Papaemmanouil, O., Peng, K., Peng, L.: Aide: an automatic user navigation system for interactive data exploration. PVLDB 8(12), 1964–1967 (2015)
7.
Dimitriadou, K., Papaemmanouil, O., Diao, Y.: Explore-by-example: an automatic query steering framework for interactive data exploration. In: SIGMOD (2014)
8.
Dimitriadou, K., Papaemmanouil, O., Diao, Y.: Aide: an active learning-based approach for interactive data exploration. IEEE Trans. Knowl. Data Eng. 28(11), 2842–2856 (2016)CrossRef
9.
Drosou, M., Pitoura, E.: Ymaldb: exploring relational databases via result-driven recommendations. VLDB J. 22(6), 849–874 (2013)CrossRef
10.
Fukuda, T., Morimoto, Y., Morishita, S., Tokuyama, T.: Mining optimized association rules for numeric attributes. In: Proceedings of the Fifteenth ACM SIGACT-SIGMOD-SIGART Symposium on Principles of Database Systems, pp 182–191. ACM (1996)
11.
Fung, G. P. C., Yu, J. X., Yu, P. S., Lu, H.: Parameter free bursty events detection in text streams. In: VLDB (2005)
12.
Griffiths, T. L., Steyvers, M.: A probabilistic approach to semantic representation. In: Proceedings of the 24th Annual Conference of the Cognitive Science Society, pp 381–386. Citeseer (2002)
13.
Griffiths, T. L., Steyvers, M.: Finding scientific topics. Proc. Natl. Acad. Sci. 101(suppl 1), 5228–5235 (2004)CrossRef
14.
Hofmann, T.: Probabilistic latent semantic indexing. In: Proceedings of the 22nd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, pp 50–57. ACM (1999)
15.
Hofmann, T.: Unsupervised learning by probabilistic latent semantic analysis. Mach. Learn. 42(1), 177–196 (2001)CrossRefMATH
16.
Jiang, L., Nandi, A.: Snaptoquery: providing interactive feedback during exploratory query specification. PVLDB 8(11), 1250–1261 (2015)
17.
Joglekar, M., Garcia-Molina, H., Parameswaran, A.: Interactive data exploration with smart drill-down. arXiv:1412.​0364 (2014)
18.
Kahng, M., Navathe, S. B., Stasko, J. T., Chau, D. H.: Interactive browsing and navigation in relational databases. arXiv:1603.​02371 (2016)
19.
Kamat, N., Jayachandran, P., Tunga, K., Nandi, A.: Distributed and interactive cube exploration. In: ICDE (2014)
20.
21.
Lappas, T., Arai, B., Platakis, M., Kotsakos, D., Gunopulos, D.: On burstiness-aware search for document sequences. In: SIGKDD (2009)
22.
Qarabaqi, B., Riedewald, M.: User-driven refinement of imprecise queries. In: ICDE (2014)
23.
Sellam, T., Kersten, M.: Fast, explainable view detection to characterize exploration queries. In: Proceedings of the 28th International Conference on Scientific and Statistical Database Management, p 20. ACM (2016)
24.
Sellam, T., Kersten, M., et al.: Meet charles, big data query advisor. In: CIDR (2013)
25.
Sellam, T., Müller, E., Kersten, M.: Semi-automated exploration of data warehouses. In: CIKM (2015)
26.
Smith, D. R.: Applications of a strategy for designing divide-and-conquer algorithms. Sci. Comput. Program. 8(3), 213–229 (1987)CrossRefMATH
27.
Soliman, M. A., Ilyas, I. F., Chang, K. C. -C.: Top-k query processing in uncertain databases. In: ICDE (2007)
28.
Tukey, J.: Exploratory data analysis. Addison-Wesley, Reading, Mass., (1977)
29.
Vartak, M., Rahman, S., Madden, S., Parameswaran, A., Polyzotis, N.: SeeDB: efficient data-driven visualization recommendations to support visual analytics. Proceedings of the VLDB Endowment 8(13), 2182–2193 (2015)CrossRef
30.
Metadata
Title
Answering unique topic queries with dynamic threshold
Authors
Huixin Ma
Zhihui Yang
Yinan Jing
Zhenying He
X. Sean Wang
Publication date
24-01-2018
Publisher
Springer US
Published in
World Wide Web / Issue 1/2019
Print ISSN: 1386-145X
Electronic ISSN: 1573-1413
DOI
https://doi.org/10.1007/s11280-018-0528-7

Other articles of this Issue 1/2019

World Wide Web 1/2019 Go to the issue

OriginalPaper

An index structure supporting rule activation in pervasive applications

Retraction Note

Retraction Note to: A joint model for analyzing topic and sentiment dynamics from large-scale online news

OriginalPaper

Attention based hierarchical LSTM network for context-aware microblog sentiment classification

OriginalPaper

Direction-based multiple views on data

OriginalPaper

User click prediction for personalized job recommendation

OriginalPaper

SmartVM: a SLA-aware microservice deployment framework

Premium Partner

    Image Credits