Skip to main content
Fachgebiete
Automobil + Motoren Bauwesen + Immobilien Business IT + Informatik Elektrotechnik + Elektronik Energie + Nachhaltigkeit Finance + Banking Management + Führung Marketing + Vertrieb Maschinenbau + Werkstoffe Versicherung + Risiko
DE
EN
Bücher
Zeitschriften
Themenseiten
Organisationspsychologie Projektmanagement Marketing Smart Manufacturing
Weitere Formate
Podcasts Webinare Technik Webinare Wirtschaft Kongresse Veranstaltungskalender Awards
Jetzt Einzelzugang starten
Zugang für Unternehmen
Referenzkunden
SLX-Digitalkonferenz: Zukunftswerkstatt 2024

Mehr Umsatz mit Top-Kontakten

Am 7. Mai erfahren Sie, wie Vertriebsteams Leadgenerierung, Leadnurturing und Leadstrategien effizient steuern können.
Erweiterte Suche
Anmelden
nach oben
Erschienen in:
Feature Point Detection and Target Tracking Based on SIFT and KLT Kapitel lesen Erstes Kapitel lesen

2018 | OriginalPaper | Buchkapitel

COKES: Continuous Top-k Keyword Search in Relational Databases

verfasst von : Yanwei Xu, Yicheng Yang

Erschienen in: Geo-Spatial Knowledge and Intelligence

Verlag: Springer Singapore

Einloggen

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config
loading …

Abstract

Keyword search in relational databases has been widely studied in recent years. Most of existing methods focus on answering snapshot keyword queries in static databases. However, in practice, relational databases are always being updated continually. Reevaluating a keyword query using existing methods after the database is updated is prohibitively expensive. In this paper we describe the COKES system, which keeps the set of answers whose upper bounds of future relevance scores are larger than a threshold for top-k answers maintenance. Experimental results show that the proposed method is efficient in answering continuous top-k keyword queries in relational databases.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

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!

Jetzt informieren

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!

Jetzt informieren

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!

Jetzt informieren
Vorheriges Kapitel An Algebraic Multigrid Preconditioner Based on Aggregation from Top to Bottom
Nächstes Kapitel Core Competencies Keywords Discovering Algorithm for Employment Advertisements
Literatur
1.
Aditya, B., Bhalotia, G., Chakrabarti, S., Hulgeri, A., Nakhe, C., Parag, P.: BANKS: browsing and keyword searching in relational databases. In: VLDB, pp. 1083–1086 (2002)CrossRef
2.
Li, G., Zhou, X., Feng, J., Wang, J.: Progressive keyword search in relational databases. In: ICDE, pp. 1183–1186 (2009)
3.
Kacholia, V., Pandit, S., Chakrabarti, S., Sudarshan, S., Desai, R., Karambelkar, H.: Bidirectional expansion for keyword search on graph databases. In: VLDB, pp. 505–516 (2005)
4.
He, H., Wang, H., Yang, J., Yu, P.S.: BLINKS: ranked keyword searches on graphs. In: ACM SIGMOD, New York, NY, USA, pp. 305–316. ACM (2007)
5.
Li, G., Ooi, B.C., Feng, J., Wang, J., Zhou, L.: EASE: an effective 3-in-1 keyword search method for unstructured, semi-structured and structured data. In: ACM SIGMOD, pp. 903–914 (2008)
6.
Agrawal, S., Chaudhuri, S., Das, G.: DBXplorer: a system for keyword-based search over relational databases. In: ICDE, pp. 5–16 (2002)
7.
Hristidisand, V., Papakonstantinou, Y.: DISCOVER: keyword search in relational databases. In: VLDB, pp. 670–681 (2002)CrossRef
8.
Hristidis, V., Gravano, L., Papakonstantinou, Y.: Efficient IR-style keyword search over relational databases. In: VLDB, pp. 850–861 (2003)CrossRef
9.
Liu, F., Yu, C., Meng, W., Chowdhury, A.: Effective keyword search in relational databases. In: ACM SIGMOD, pp. 563–574 (2006)
10.
Luo, Y., Lin, X., Wang, W., Zhou, X.: SPARK: top-k keyword query in relational databases. In: ACM SIGMOD, pp. 115–126 (2007)
11.
Yu, J.X., Qin, L., Chang, L.: Keyword search in relational databases: a survey. Bull. IEEE Tech. Committee Data Eng. 33(10), 67–78 (2010)
12.
Luo, Y.: SPARK: A Keyword Search System on Relational Databases, Ph.D. thesis, The University of New South Wales (2009)
13.
14.
Fagin, R., Lotem, A., Naor, M.: Optimal aggregation algorithms for middleware. J. Comput. Syst. Sci. 66(4), 614–656 (2003)MathSciNetCrossRef
15.
Burns, A.: Preemptive priority-based scheduling: an appropriate engineering approach. In: Advances in real-time systems, pp. 225–248 (1995)
16.
Zeng, Z., Bao, Z., Ling, T.W., Lee, M.L.: iSearch: an interpretation based framework for keyword search in relational databases. In: KEYS, pp. 3–10 (2012)
17.
18.
Xu, Y., Guan, J., Li, F., Zhou, S.: Scalable continual top-k keyword search in relational databases. Data Knowl. Eng. 86, 206–223 (2013)CrossRef
19.
de Oliveira, P., da Silva, A.S., de Moura, E.S.: Ranking candidate networks of relations to improve keyword search over relational databases. In: 31st IEEE International Conference on Data Engineering, ICDE 2015, Seoul, South Korea, 13–17 April 2015, pp. 399–410 (2015)
20.
Zeng, Z., Bao, Z., Lee, M., Ling, T.W.: Towards an interactive keyword search over relational databases. In: Proceedings of the 24th International Conference on World Wide Web Companion, WWW 2015, Florence, Italy, 18–22 May 2015, Companion Volume, pp. 259–262 (2015)
21.
Kargar, M., An, A., Cercone, N., Godfrey, P., Szlichta, J., Yu, X.: Meaningful keyword search in relational databases with large and complex schema. In: 31st IEEE International Conference on Data Engineering, ICDE 2015, Seoul, South Korea, 13–17 April 2015, pp. 411–422 (2015)
22.
Zhou, J., Liu, Y., Yu, Z.: Improving the effectiveness of keyword search in databases using query logs. In: Proceedings of 16th International Conference on Web-Age Information Management, WAIM 2015, Qingdao, China, 8–10 June 2015, pp. 193–206 (2015)CrossRef
23.
Ling, T.W., Le, T.N., Zeng, Z.: Towards an intelligent keyword search over XML and relational databases. In: International Conference on Big Data and Smart Computing, BIGCOMP 2014, Bangkok, Thailand, 15–17 January 2014, pp. 1–6 (2014)
24.
Torlone, R.: Towards a new foundation for keyword search in relational databases. In: Proceedings of the 8th Alberto Mendelzon Workshop on Foundations of Data Management, Cartagena de Indias, Colombia, 4–6 June 2014 (2014)
25.
Lin, Z., Li, Y., Lai, Y.: Improve the effectiveness of keyword search over relational database by node-temperature-based ant colony optimization. In: 12th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2015, Zhangjiajie, China, 15–17 August 2015, pp. 1209–1214 (2015)
26.
Ling, T.W., Zeng, Z., Le, T.N., Lee, M.: Ora-semantics based keyword search in XML and relational databases. In: 32nd IEEE International Conference on Data Engineering Workshops, ICDE Workshops 2016, Helsinki, Finland, 16–20 May 2016, pp. 157–160 (2016)
27.
Yu, Z., Yu, X., Chen, Y., Ma, K.: Distributed top-k keyword search over very large databases with map reduce. In: 2016 IEEE International Congress on Big Data, San Francisco, CA, USA, June 27–July 2 2016, pp. 349–352 (2016)
28.
Qin, L., Yu, J.X., Chang, L., Tao, Y.: Querying communities in relational databases. In: ICDE, pp. 724–735 (2009)
29.
Jaehui, P., Sang-goo, L.: Keyword search in relational databases. Knowl. Inf. Syst. 26(2), 175–193 (2011)CrossRef
30.
Markowetz, A., Yang, Y., Papadias, D.: Keyword search on relational data streams. In: ACM SIGMOD, pp. 605–616 (2007)
31.
Qin, L., Yu, J.X., Chang, L., Tao, Y.: Scalable keyword search on large data streams. In: ICDE, pp. 1199–1202 (2009)
Metadaten
Titel
COKES: Continuous Top-k Keyword Search in Relational Databases
verfasst von
Yanwei Xu
Yicheng Yang
Copyright-Jahr
2018
Verlag
Springer Singapore
Buch
Geo-Spatial Knowledge and Intelligence

Print ISBN: 978-981-13-0895-6

Electronic ISBN: 978-981-13-0896-3

Copyright-Jahr: 2018

DOI
https://doi.org/10.1007/978-981-13-0896-3_21